2019-01-18 02:04:57 2019-01-18 02:04:57 R version 3.5.1 (2018-07-02) -- "Feather Spray" 2019-01-18 02:04:57 Copyright (C) 2018 The R Foundation for Statistical Computing 2019-01-18 02:04:57 Platform: x86_64-pc-linux-gnu (64-bit) 2019-01-18 02:04:57 2019-01-18 02:04:57 R is free software and comes with ABSOLUTELY NO WARRANTY. 2019-01-18 02:04:57 You are welcome to redistribute it under certain conditions. 2019-01-18 02:04:57 Type 'license()' or 'licence()' for distribution details. 2019-01-18 02:04:57 2019-01-18 02:04:57 Natural language support but running in an English locale 2019-01-18 02:04:57 2019-01-18 02:04:57 R is a collaborative project with many contributors. 2019-01-18 02:04:57 Type 'contributors()' for more information and 2019-01-18 02:04:57 'citation()' on how to cite R or R packages in publications. 2019-01-18 02:04:57 2019-01-18 02:04:57 Type 'demo()' for some demos, 'help()' for on-line help, or 2019-01-18 02:04:57 'help.start()' for an HTML browser interface to help. 2019-01-18 02:04:57 Type 'q()' to quit R. 2019-01-18 02:04:57 2019-01-18 02:04:57 > setwd( Sys.getenv( "RWD" ) ) 2019-01-18 02:04:57 > a <- lodown::get_catalog("censo") 2019-01-18 02:04:57 building catalog for censo 2019-01-18 02:04:57 2019-01-18 02:05:03 > # don't do 2000 it's been broken forever 2019-01-18 02:05:03 > lodown::lodown("censo", catalog=a[a$year == 2010,], output_dir= getwd()) 2019-01-18 02:05:03 locally downloading censo 2019-01-18 02:05:03 2019-01-18 02:05:08 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/AC.zip' 2019-01-18 02:05:08 cached in 2019-01-18 02:05:08 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/8d33c41dcfde91034b1afbc3105bd061.Rcache' 2019-01-18 02:05:08 copying to 2019-01-18 02:05:08 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/Rtmpd0144A/file11421f452bc2' 2019-01-18 02:05:08 2019-01-18 02:05:22 censo catalog entry 1 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484/MonetDB' 2019-01-18 02:05:22 2019-01-18 02:14:43 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/AL.zip' 2019-01-18 02:14:43 cached in 2019-01-18 02:14:43 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/675d0405924a1b73a6f889f953a759ab.Rcache' 2019-01-18 02:14:43 copying to 2019-01-18 02:14:43 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/Rtmpd0144A/file11421f452bc2' 2019-01-18 02:14:43 2019-01-18 02:39:59 censo catalog entry 2 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484/MonetDB' 2019-01-18 02:39:59 2019-01-18 02:43:29 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/AM.zip' 2019-01-18 02:43:29 cached in 2019-01-18 02:43:29 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/8a1e7a9111551585f7cec0b7b767e0c7.Rcache' 2019-01-18 02:43:29 copying to 2019-01-18 02:43:29 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/Rtmpd0144A/file11421f452bc2' 2019-01-18 02:43:29 2019-01-18 03:01:13 censo catalog entry 3 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484/MonetDB' 2019-01-18 03:01:13 2019-01-18 03:11:04 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/AP.zip' 2019-01-18 03:11:04 cached in 2019-01-18 03:11:04 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/6eeff2ce0144bb14d5a56c6ca27fcdf9.Rcache' 2019-01-18 03:11:04 copying to 2019-01-18 03:11:04 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/Rtmpd0144A/file11421f452bc2' 2019-01-18 03:11:04 2019-01-18 03:12:15 censo catalog entry 4 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484/MonetDB' 2019-01-18 03:12:15 2019-01-18 03:40:56 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/BA.zip' 2019-01-18 03:40:56 cached in 2019-01-18 03:40:56 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/f12488e852651d05e153bb9f21b670ed.Rcache' 2019-01-18 03:40:56 copying to 2019-01-18 03:40:56 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/Rtmpd0144A/file11421f452bc2' 2019-01-18 03:40:56 2019-01-18 03:54:00 censo catalog entry 5 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484/MonetDB' 2019-01-18 03:54:00 2019-01-18 03:56:24 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/CE.zip' 2019-01-18 03:56:24 cached in 2019-01-18 03:56:24 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/6e5d97ea080321a3f736da278ccb0c36.Rcache' 2019-01-18 03:56:24 copying to 2019-01-18 03:56:24 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/Rtmpd0144A/file11421f452bc2' 2019-01-18 03:56:24 2019-01-18 04:05:08 censo catalog entry 6 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484/MonetDB' 2019-01-18 04:05:08 2019-01-18 04:07:29 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/DF.zip' 2019-01-18 04:07:29 cached in 2019-01-18 04:07:29 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/31c64b57fe5442cb7c07b351e8c5a51c.Rcache' 2019-01-18 04:07:29 copying to 2019-01-18 04:07:29 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/Rtmpd0144A/file11421f452bc2' 2019-01-18 04:07:29 2019-01-18 04:09:10 censo catalog entry 7 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484/MonetDB' 2019-01-18 04:09:10 2019-01-18 06:40:45 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/ES.zip' 2019-01-18 06:40:45 cached in 2019-01-18 06:40:45 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/b751b8a9e5ee7aa58c52b86c25bd041e.Rcache' 2019-01-18 06:40:45 copying to 2019-01-18 06:40:45 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/Rtmpd0144A/file11421f452bc2' 2019-01-18 06:40:45 2019-01-18 06:46:05 censo catalog entry 8 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484/MonetDB' 2019-01-18 06:46:05 2019-01-18 06:49:50 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/GO.zip' 2019-01-18 06:49:50 cached in 2019-01-18 06:49:50 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/f29a3850a4b737df7e2e8ea62f0007b9.Rcache' 2019-01-18 06:49:50 copying to 2019-01-18 06:49:50 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/Rtmpd0144A/file11421f452bc2' 2019-01-18 06:49:50 2019-01-18 06:57:03 censo catalog entry 9 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484/MonetDB' 2019-01-18 06:57:03 2019-01-18 06:59:00 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/MA.zip' 2019-01-18 06:59:00 cached in 2019-01-18 06:59:00 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/362a6e810463c8a0e38517f5163cc222.Rcache' 2019-01-18 06:59:00 copying to 2019-01-18 06:59:00 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/Rtmpd0144A/file11421f452bc2' 2019-01-18 06:59:00 2019-01-18 07:04:28 censo catalog entry 10 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484/MonetDB' 2019-01-18 07:04:28 2019-01-18 07:07:13 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/MG.zip' 2019-01-18 07:07:13 cached in 2019-01-18 07:07:13 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/90c71c4f917ad6d89d0f453c2e3c2dc9.Rcache' 2019-01-18 07:07:13 copying to 2019-01-18 07:07:13 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/Rtmpd0144A/file11421f452bc2' 2019-01-18 07:07:13 2019-01-18 07:33:52 censo catalog entry 11 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484/MonetDB' 2019-01-18 07:33:52 2019-01-18 07:38:41 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/MS.zip' 2019-01-18 07:38:41 cached in 2019-01-18 07:38:41 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/b5e5b1b9e2e979e74c9ec72feec10865.Rcache' 2019-01-18 07:38:41 copying to 2019-01-18 07:38:41 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/Rtmpd0144A/file11421f452bc2' 2019-01-18 07:38:41 2019-01-18 07:52:26 censo catalog entry 12 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484/MonetDB' 2019-01-18 07:52:26 2019-01-18 08:11:41 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/MT.zip' 2019-01-18 08:11:41 cached in 2019-01-18 08:11:41 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/86f0b09d2b55f9efa586af32e4f2314a.Rcache' 2019-01-18 08:11:41 copying to 2019-01-18 08:11:41 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/Rtmpd0144A/file11421f452bc2' 2019-01-18 08:11:41 2019-01-18 08:30:43 censo catalog entry 13 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484/MonetDB' 2019-01-18 08:30:43 2019-01-18 08:45:17 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/PA.zip' 2019-01-18 08:45:17 cached in 2019-01-18 08:45:17 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/738b3f4e5c93d2280a8b0a744134c648.Rcache' 2019-01-18 08:45:17 copying to 2019-01-18 08:45:17 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/Rtmpd0144A/file11421f452bc2' 2019-01-18 08:45:17 2019-01-18 09:24:18 censo catalog entry 14 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484/MonetDB' 2019-01-18 09:24:18 2019-01-18 09:33:32 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/PB.zip' 2019-01-18 09:33:32 cached in 2019-01-18 09:33:32 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/8bd47199975bdf2964c09aa4e21648e1.Rcache' 2019-01-18 09:33:32 copying to 2019-01-18 09:33:32 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/Rtmpd0144A/file11421f452bc2' 2019-01-18 09:33:32 2019-01-18 10:56:01 censo catalog entry 15 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484/MonetDB' 2019-01-18 10:56:10 2019-01-18 11:33:16 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/PE.zip' 2019-01-18 11:33:16 cached in 2019-01-18 11:33:16 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/eac1739962da73a00dfb693f03377c92.Rcache' 2019-01-18 11:33:16 copying to 2019-01-18 11:33:16 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/Rtmpd0144A/file11421f452bc2' 2019-01-18 11:33:16 2019-01-18 11:44:48 censo catalog entry 16 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484/MonetDB' 2019-01-18 11:44:48 2019-01-18 11:46:40 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/PI.zip' 2019-01-18 11:46:40 cached in 2019-01-18 11:46:40 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/06c1460710d6b2b70933afe955bf06ee.Rcache' 2019-01-18 11:46:40 copying to 2019-01-18 11:46:40 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/Rtmpd0144A/file11421f452bc2' 2019-01-18 11:46:40 2019-01-18 12:23:03 censo catalog entry 17 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484/MonetDB' 2019-01-18 12:23:03 2019-01-18 12:24:36 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/PR.zip' 2019-01-18 12:24:36 cached in 2019-01-18 12:24:36 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/409a9525b7a91b4618baf65cc89dce07.Rcache' 2019-01-18 12:24:36 copying to 2019-01-18 12:24:36 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/Rtmpd0144A/file11421f452bc2' 2019-01-18 12:24:36 2019-01-18 12:32:23 censo catalog entry 18 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484/MonetDB' 2019-01-18 12:32:23 2019-01-18 12:37:23 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/RJ.zip' 2019-01-18 12:37:23 cached in 2019-01-18 12:37:23 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/5b82d082ec19bfb478942334dee06362.Rcache' 2019-01-18 12:37:23 copying to 2019-01-18 12:37:23 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/Rtmpd0144A/file11421f452bc2' 2019-01-18 12:37:23 2019-01-18 12:57:40 censo catalog entry 19 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484/MonetDB' 2019-01-18 12:57:40 2019-01-18 12:59:54 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/RN.zip' 2019-01-18 12:59:54 cached in 2019-01-18 12:59:54 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/791786e4d34a82d9602a9782cfcf56ee.Rcache' 2019-01-18 12:59:54 copying to 2019-01-18 12:59:54 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/Rtmpd0144A/file11421f452bc2' 2019-01-18 12:59:54 2019-01-18 13:14:17 censo catalog entry 20 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484/MonetDB' 2019-01-18 13:14:17 2019-01-18 13:25:32 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/RO.zip' 2019-01-18 13:25:32 cached in 2019-01-18 13:25:32 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/d1e8db0e4c49bf7785e6765a73a0ef97.Rcache' 2019-01-18 13:25:32 copying to 2019-01-18 13:25:32 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/Rtmpd0144A/file11421f452bc2' 2019-01-18 13:25:32 2019-01-18 13:59:44 censo catalog entry 21 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484/MonetDB' 2019-01-18 13:59:44 2019-01-18 14:02:24 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/RR.zip' 2019-01-18 14:02:24 cached in 2019-01-18 14:02:24 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/30da4639719883b3e680399fe5f3f7c5.Rcache' 2019-01-18 14:02:24 copying to 2019-01-18 14:02:24 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/Rtmpd0144A/file11421f452bc2' 2019-01-18 14:02:24 2019-01-18 14:02:42 censo catalog entry 22 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484/MonetDB' 2019-01-18 14:02:42 2019-01-18 14:28:07 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/RS.zip' 2019-01-18 14:28:07 cached in 2019-01-18 14:28:07 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/989abcab6ef8f4cc0482c4da694d254e.Rcache' 2019-01-18 14:28:07 copying to 2019-01-18 14:28:07 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/Rtmpd0144A/file11421f452bc2' 2019-01-18 14:28:07 2019-01-18 15:25:40 censo catalog entry 23 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484/MonetDB' 2019-01-18 15:25:40 2019-01-18 15:29:15 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/SC.zip' 2019-01-18 15:29:15 cached in 2019-01-18 15:29:15 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/5aa8eea1b7368218b7503d61f196b586.Rcache' 2019-01-18 15:29:15 copying to 2019-01-18 15:29:15 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/Rtmpd0144A/file11421f452bc2' 2019-01-18 15:29:15 2019-01-18 15:33:18 censo catalog entry 24 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484/MonetDB' 2019-01-18 15:33:18 2019-01-18 15:38:13 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/SE.zip' 2019-01-18 15:38:13 cached in 2019-01-18 15:38:13 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/af4222637a1c8e705f816d7a78284a2f.Rcache' 2019-01-18 15:38:13 copying to 2019-01-18 15:38:13 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/Rtmpd0144A/file11421f452bc2' 2019-01-18 15:38:13 2019-01-18 16:12:58 censo catalog entry 25 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484/MonetDB' 2019-01-18 16:12:58 2019-01-18 16:18:45 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/SP1.zip' 2019-01-18 16:18:45 cached in 2019-01-18 16:18:45 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/5493bb945da3b02e07808de8b2c38054.Rcache' 2019-01-18 16:18:45 copying to 2019-01-18 16:18:45 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/Rtmpd0144A/file11421f452bc2' 2019-01-18 16:18:45 2019-01-18 16:27:25 censo catalog entry 26 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484/MonetDB' 2019-01-18 16:27:25 2019-01-18 16:29:48 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/SP2_RM.zip' 2019-01-18 16:29:48 cached in 2019-01-18 16:29:48 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/688c1a930ab09e425507f8e308e0d3cc.Rcache' 2019-01-18 16:29:48 copying to 2019-01-18 16:29:48 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/Rtmpd0144A/file11421f452bc2' 2019-01-18 16:29:48 2019-01-18 16:43:47 censo catalog entry 27 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484/MonetDB' 2019-01-18 16:43:47 2019-01-18 16:50:59 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/TO.zip' 2019-01-18 16:50:59 cached in 2019-01-18 16:50:59 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/319c75b43a1d30166e3a0185c3a7d1ad.Rcache' 2019-01-18 16:50:59 copying to 2019-01-18 16:50:59 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/Rtmpd0144A/file11421f452bc2' 2019-01-18 16:50:59 2019-01-18 17:09:25 censo catalog entry 28 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484/MonetDB' 2019-01-18 17:09:25 2019-01-18 18:08:26 censo survey design entry 1 of 2 stored at '/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484/dom 2010 design.rds' 2019-01-18 18:08:26 2019-01-18 21:25:04 censo survey design entry 2 of 2 stored at '/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484/pes 2010 design.rds' 2019-01-18 21:25:06 2019-01-18 21:25:06 censo local download completed 2019-01-18 21:25:06 2019-01-18 21:25:07 Warning message: 2019-01-18 21:25:07 In .Internal(gc(verbose, reset, full)) : 2019-01-18 21:25:07 Connection is garbage-collected, use dbDisconnect() to avoid this. 2019-01-18 21:25:07 > setup return code=0 2019-01-18 21:25:12 2019-01-18 21:25:12 R version 3.5.1 (2018-07-02) -- "Feather Spray" 2019-01-18 21:25:12 Copyright (C) 2018 The R Foundation for Statistical Computing 2019-01-18 21:25:12 Platform: x86_64-pc-linux-gnu (64-bit) 2019-01-18 21:25:12 2019-01-18 21:25:12 R is free software and comes with ABSOLUTELY NO WARRANTY. 2019-01-18 21:25:12 You are welcome to redistribute it under certain conditions. 2019-01-18 21:25:12 Type 'license()' or 'licence()' for distribution details. 2019-01-18 21:25:12 2019-01-18 21:25:12 Natural language support but running in an English locale 2019-01-18 21:25:12 2019-01-18 21:25:12 R is a collaborative project with many contributors. 2019-01-18 21:25:12 Type 'contributors()' for more information and 2019-01-18 21:25:12 'citation()' on how to cite R or R packages in publications. 2019-01-18 21:25:12 2019-01-18 21:25:12 Type 'demo()' for some demos, 'help()' for on-line help, or 2019-01-18 21:25:12 'help.start()' for an HTML browser interface to help. 2019-01-18 21:25:12 Type 'q()' to quit R. 2019-01-18 21:25:12 2019-01-18 21:25:13 > setwd( Sys.getenv( "RWD" ) ) 2019-01-18 21:25:13 > 2019-01-18 21:25:13 > machine_specific_replacements <- 2019-01-18 21:25:13 + list( 2019-01-18 21:25:13 + 2019-01-18 21:25:13 + # replace the folder path on macnix 2019-01-18 21:25:13 + c( 'path.expand( \"~\" ) , \"CENSO\"' , paste0( '"' , getwd() , '"' ) ) , 2019-01-18 21:25:13 + 2019-01-18 21:25:13 + # change other things in the script to be run 2019-01-18 21:25:13 + c( "hello" , "howdy" ) 2019-01-18 21:25:13 + 2019-01-18 21:25:13 + ) 2019-01-18 21:25:13 > 2019-01-18 21:25:13 > source( lodown::syntaxtractor( "censo" , replacements = machine_specific_replacements , setup_test = "test" ) , echo = TRUE ) 2019-01-18 21:25:14 2019-01-18 21:25:14 > library(lodown) 2019-01-18 21:25:14 2019-01-18 21:25:14 > censo_cat <- get_catalog("censo", output_dir = file.path("/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484")) 2019-01-18 21:25:14 building catalog for censo 2019-01-18 21:25:14 2019-01-18 21:25:21 2019-01-18 21:25:21 > censo_cat <- subset(censo_cat, year == 2010) 2019-01-18 21:25:21 2019-01-18 21:25:21 > stopifnot(nrow(censo_cat) > 0) 2019-01-18 21:25:21 2019-01-18 21:25:21 > library(DBI) 2019-01-18 21:25:21 2019-01-18 21:25:21 > library(MonetDBLite) 2019-01-18 21:25:26 2019-01-18 21:25:26 > library(survey) 2019-01-18 21:25:26 Loading required package: grid 2019-01-18 21:25:26 Loading required package: Matrix 2019-01-18 21:25:27 Loading required package: survival 2019-01-18 21:25:27 2019-01-18 21:25:27 Attaching package: ‘survey’ 2019-01-18 21:25:27 2019-01-18 21:25:27 The following object is masked from ‘package:graphics’: 2019-01-18 21:25:27 2019-01-18 21:25:27 dotchart 2019-01-18 21:25:27 2019-01-18 21:25:27 2019-01-18 21:25:27 > options(survey.lonely.psu = "adjust") 2019-01-18 21:25:27 2019-01-18 21:25:27 > censo_design <- readRDS(file.path("/export/scratch1/home/hannes/eanthony/r-wd/censo-1547773484", 2019-01-18 21:25:27 + "pes 2010 design.rds")) 2019-01-18 21:25:52 2019-01-18 21:25:52 > censo_design <- open(censo_design, driver = MonetDBLite()) 2019-01-18 21:32:32 2019-01-18 21:32:35 > censo_design <- update(censo_design, nmorpob1 = ifelse(v6531 >= 2019-01-18 21:32:35 + 0, as.numeric(v6531 < 70), NA), nmorpob2 = ifelse(v6531 >= 2019-01-18 21:32:35 + 0, as.numer .... [TRUNCATED] 2019-01-18 21:32:35 2019-01-18 21:32:35 > sum(weights(censo_design, "sampling") != 0) 2019-01-18 21:32:35 [1] 20635472 2019-01-18 21:32:35 2019-01-18 21:32:35 > svyby(~one, ~state_name, censo_design, unwtd.count) 2019-01-18 21:32:35 QQ: 'SELECT 1' 2019-01-18 21:32:35 II: Finished in 0s 2019-01-18 21:32:35 QQ: 'select one from c10' 2019-01-18 21:32:35 II: Finished in 0s 2019-01-18 21:32:35 QQ: 'SELECT 1' 2019-01-18 21:32:35 II: Finished in 0s 2019-01-18 21:32:35 QQ: 'select v0001 from c10' 2019-01-18 21:32:39 II: Finished in 6.93s 2019-01-18 21:36:20 state_name counts se 2019-01-18 21:36:20 Rondonia Rondonia 195607 0 2019-01-18 21:36:20 Acre Acre 93675 0 2019-01-18 21:36:20 Amazonas Amazonas 295034 0 2019-01-18 21:36:20 Roraima Roraima 63765 0 2019-01-18 21:36:20 Para Para 729094 0 2019-01-18 21:36:20 Amapa Amapa 78344 0 2019-01-18 21:36:20 Tocantins Tocantins 267745 0 2019-01-18 21:36:20 Maranhao Maranhao 793241 0 2019-01-18 21:36:20 Piaui Piaui 496477 0 2019-01-18 21:36:20 Ceara Ceara 846164 0 2019-01-18 21:36:20 Rio Grande do Norte Rio Grande do Norte 424586 0 2019-01-18 21:36:20 Paraiba Paraiba 571631 0 2019-01-18 21:36:20 Pernambuco Pernambuco 892250 0 2019-01-18 21:36:20 Alagoas Alagoas 349966 0 2019-01-18 21:36:20 Sergipe Sergipe 245354 0 2019-01-18 21:36:20 Bahia Bahia 1550842 0 2019-01-18 21:36:20 Minas Gerais Minas Gerais 2506265 0 2019-01-18 21:36:20 Espirito Santo Espirito Santo 400130 0 2019-01-18 21:36:20 Rio de Janeiro Rio de Janeiro 1143650 0 2019-01-18 21:36:20 Sao Paulo Sao Paulo 3651181 0 2019-01-18 21:36:20 Parana Parana 1293034 0 2019-01-18 21:36:20 Santa Catarina Santa Catarina 872242 0 2019-01-18 21:36:20 Rio Grande do Sul Rio Grande do Sul 1388443 0 2019-01-18 21:36:20 Mato Grosso do Sul Mato Grosso do Sul 276714 0 2019-01-18 21:36:20 Mato Grosso Mato Grosso 386537 0 2019-01-18 21:36:20 Goias Goias 707043 0 2019-01-18 21:36:20 Distrito Federal Distrito Federal 116458 0 2019-01-18 21:36:20 2019-01-18 21:36:20 > svytotal(~one, censo_design) 2019-01-18 21:36:20 QQ: 'SELECT 1' 2019-01-18 21:36:20 II: Finished in 0s 2019-01-18 21:36:20 QQ: 'select one from c10' 2019-01-18 21:36:20 II: Finished in 0s 2019-01-18 21:36:49 total SE 2019-01-18 21:36:49 one 190755799 54683 2019-01-18 21:36:49 2019-01-18 21:36:49 > svyby(~one, ~state_name, censo_design, svytotal) 2019-01-18 21:36:49 QQ: 'SELECT 1' 2019-01-18 21:36:49 II: Finished in 0s 2019-01-18 21:36:49 QQ: 'select one from c10' 2019-01-18 21:36:49 II: Finished in 0s 2019-01-18 21:36:49 QQ: 'SELECT 1' 2019-01-18 21:36:49 II: Finished in 0s 2019-01-18 21:36:49 QQ: 'select v0001 from c10' 2019-01-18 21:36:49 II: Finished in 0.2s 2019-01-18 21:40:32 state_name one se 2019-01-18 21:40:32 Rondonia Rondonia 1562409 3948.137 2019-01-18 21:40:32 Acre Acre 733559 2791.782 2019-01-18 21:40:32 Amazonas Amazonas 3483985 9212.177 2019-01-18 21:40:32 Roraima Roraima 450479 2360.628 2019-01-18 21:40:32 Para Para 7581051 12687.834 2019-01-18 21:40:32 Amapa Amapa 669526 3553.561 2019-01-18 21:40:32 Tocantins Tocantins 1383445 3525.848 2019-01-18 21:40:32 Maranhao Maranhao 6574789 9181.269 2019-01-18 21:40:32 Piaui Piaui 3118360 5279.586 2019-01-18 21:40:32 Ceara Ceara 8452381 11033.966 2019-01-18 21:40:32 Rio Grande do Norte Rio Grande do Norte 3168027 6096.634 2019-01-18 21:40:32 Paraiba Paraiba 3766528 6185.208 2019-01-18 21:40:32 Pernambuco Pernambuco 8796448 10518.912 2019-01-18 21:40:32 Alagoas Alagoas 3120494 7245.763 2019-01-18 21:40:32 Sergipe Sergipe 2068017 4781.781 2019-01-18 21:40:32 Bahia Bahia 14016906 12716.460 2019-01-18 21:40:32 Minas Gerais Minas Gerais 19597330 14944.336 2019-01-18 21:40:32 Espirito Santo Espirito Santo 3514952 5294.570 2019-01-18 21:40:32 Rio de Janeiro Rio de Janeiro 15989929 15402.140 2019-01-18 21:40:32 Sao Paulo Sao Paulo 41262199 22915.041 2019-01-18 21:40:32 Parana Parana 10444526 9959.317 2019-01-18 21:40:32 Santa Catarina Santa Catarina 6248436 6055.257 2019-01-18 21:40:32 Rio Grande do Sul Rio Grande do Sul 10693929 11156.591 2019-01-18 21:40:32 Mato Grosso do Sul Mato Grosso do Sul 2449024 4997.959 2019-01-18 21:40:32 Mato Grosso Mato Grosso 3035122 6705.408 2019-01-18 21:40:32 Goias Goias 6003788 8616.152 2019-01-18 21:40:32 Distrito Federal Distrito Federal 2570160 7562.860 2019-01-18 21:40:32 2019-01-18 21:40:32 > svymean(~v6033, censo_design) 2019-01-18 21:40:32 QQ: 'SELECT 1' 2019-01-18 21:42:17 II: Finished in 1.75s 2019-01-18 21:42:18 QQ: 'select v6033 from c10' 2019-01-18 21:42:18 II: Finished in 0s 2019-01-18 21:42:49 mean SE 2019-01-18 21:42:52 v6033 44.532 0.0291 2019-01-18 21:42:52 2019-01-18 21:42:52 > svyby(~v6033, ~state_name, censo_design, svymean) 2019-01-18 21:42:52 QQ: 'SELECT 1' 2019-01-18 21:42:52 II: Finished in 0s 2019-01-18 21:42:52 QQ: 'select v6033 from c10' 2019-01-18 21:42:52 II: Finished in 0s 2019-01-18 21:42:52 QQ: 'SELECT 1' 2019-01-18 21:42:52 II: Finished in 0s 2019-01-18 21:42:52 QQ: 'select v0001 from c10' 2019-01-18 21:42:52 II: Finished in 0.2s 2019-01-18 21:46:29 state_name v6033 se 2019-01-18 21:46:29 Rondonia Rondonia 43.47609 0.29255813 2019-01-18 21:46:29 Acre Acre 44.14539 0.42900430 2019-01-18 21:46:29 Amazonas Amazonas 44.89294 0.26248045 2019-01-18 21:46:29 Roraima Roraima 44.61115 0.48059649 2019-01-18 21:46:29 Para Para 44.06793 0.12801155 2019-01-18 21:46:29 Amapa Amapa 44.36371 0.47275275 2019-01-18 21:46:29 Tocantins Tocantins 44.08827 0.24578628 2019-01-18 21:46:29 Maranhao Maranhao 44.39162 0.14799628 2019-01-18 21:46:29 Piaui Piaui 44.23805 0.20966135 2019-01-18 21:46:29 Ceara Ceara 43.97193 0.12519040 2019-01-18 21:46:29 Rio Grande do Norte Rio Grande do Norte 44.05621 0.18677314 2019-01-18 21:46:29 Paraiba Paraiba 45.40817 0.17778339 2019-01-18 21:46:29 Pernambuco Pernambuco 44.35515 0.12297141 2019-01-18 21:46:29 Alagoas Alagoas 44.39060 0.21888708 2019-01-18 21:46:29 Sergipe Sergipe 43.67018 0.26465445 2019-01-18 21:46:29 Bahia Bahia 44.00062 0.09072600 2019-01-18 21:46:29 Minas Gerais Minas Gerais 44.22639 0.07945220 2019-01-18 21:46:29 Espirito Santo Espirito Santo 44.43069 0.18252646 2019-01-18 21:46:29 Rio de Janeiro Rio de Janeiro 45.11529 0.08475508 2019-01-18 21:46:29 Sao Paulo Sao Paulo 44.86147 0.06044199 2019-01-18 21:46:29 Parana Parana 44.88411 0.11843766 2019-01-18 21:46:29 Santa Catarina Santa Catarina 44.42404 0.11024326 2019-01-18 21:46:29 Rio Grande do Sul Rio Grande do Sul 45.18820 0.10302228 2019-01-18 21:46:29 Mato Grosso do Sul Mato Grosso do Sul 45.08575 0.22239028 2019-01-18 21:46:29 Mato Grosso Mato Grosso 43.70309 0.22561486 2019-01-18 21:46:29 Goias Goias 44.16120 0.15141651 2019-01-18 21:46:29 Distrito Federal Distrito Federal 43.61118 0.29819552 2019-01-18 21:46:29 2019-01-18 21:46:29 > svymean(~sexo, censo_design) 2019-01-18 21:46:29 QQ: 'SELECT 1' 2019-01-18 21:46:29 II: Finished in 0s 2019-01-18 21:46:29 QQ: 'select v0601 from c10' 2019-01-18 21:46:29 II: Finished in 0.47s 2019-01-18 21:47:03 mean SE 2019-01-18 21:47:03 sexomasculino 0.48967 1e-04 2019-01-18 21:47:03 sexofeminino 0.51033 1e-04 2019-01-18 21:47:03 2019-01-18 21:47:03 > svyby(~sexo, ~state_name, censo_design, svymean) 2019-01-18 21:47:03 QQ: 'SELECT 1' 2019-01-18 21:47:03 II: Finished in 0s 2019-01-18 21:47:03 QQ: 'select v0601 from c10' 2019-01-18 21:47:03 II: Finished in 0.13s 2019-01-18 21:47:03 QQ: 'SELECT 1' 2019-01-18 21:47:03 II: Finished in 0s 2019-01-18 21:47:03 QQ: 'select v0001 from c10' 2019-01-18 21:47:03 II: Finished in 0.14s 2019-01-18 21:50:45 state_name sexomasculino sexofeminino se1 2019-01-18 21:50:45 Rondonia Rondonia 0.5089301 0.4910699 0.0009246556 2019-01-18 21:50:45 Acre Acre 0.5021055 0.4978945 0.0014674090 2019-01-18 21:50:45 Amazonas Amazonas 0.5032108 0.4967892 0.0008076088 2019-01-18 21:50:45 Roraima Roraima 0.5080348 0.4919652 0.0019616397 2019-01-18 21:50:45 Para Para 0.5041302 0.4958698 0.0005560644 2019-01-18 21:50:45 Amapa Amapa 0.5005556 0.4994444 0.0015394051 2019-01-18 21:50:45 Tocantins Tocantins 0.5077354 0.4922646 0.0007904260 2019-01-18 21:50:45 Maranhao Maranhao 0.4960638 0.5039362 0.0005031827 2019-01-18 21:50:45 Piaui Piaui 0.4901365 0.5098635 0.0008290869 2019-01-18 21:50:45 Ceara Ceara 0.4874470 0.5125530 0.0004497972 2019-01-18 21:50:45 Rio Grande do Norte Rio Grande do Norte 0.4889122 0.5110878 0.0008851713 2019-01-18 21:50:45 Paraiba Paraiba 0.4843662 0.5156338 0.0006584047 2019-01-18 21:50:45 Pernambuco Pernambuco 0.4809533 0.5190467 0.0004462012 2019-01-18 21:50:45 Alagoas Alagoas 0.4844640 0.5155360 0.0008115701 2019-01-18 21:50:45 Sergipe Sergipe 0.4859926 0.5140074 0.0009918646 2019-01-18 21:50:45 Bahia Bahia 0.4907121 0.5092879 0.0003474925 2019-01-18 21:50:45 Minas Gerais Minas Gerais 0.4919995 0.5080005 0.0003056574 2019-01-18 21:50:45 Espirito Santo Espirito Santo 0.4925296 0.5074704 0.0006574212 2019-01-18 21:50:45 Rio de Janeiro Rio de Janeiro 0.4769051 0.5230949 0.0004261408 2019-01-18 21:50:45 Sao Paulo Sao Paulo 0.4865924 0.5134076 0.0002162530 2019-01-18 21:50:45 Parana Parana 0.4912615 0.5087385 0.0003264035 2019-01-18 21:50:45 Santa Catarina Santa Catarina 0.4961818 0.5038182 0.0004534673 2019-01-18 21:50:45 Rio Grande do Sul Rio Grande do Sul 0.4867301 0.5132699 0.0003719678 2019-01-18 21:50:45 Mato Grosso do Sul Mato Grosso do Sul 0.4981282 0.5018718 0.0009235700 2019-01-18 21:50:45 Mato Grosso Mato Grosso 0.5105350 0.4894650 0.0007216342 2019-01-18 21:50:45 Goias Goias 0.4966243 0.5033757 0.0005157195 2019-01-18 21:50:45 Distrito Federal Distrito Federal 0.4781337 0.5218663 0.0011208914 2019-01-18 21:50:45 se2 2019-01-18 21:50:45 Rondonia 0.0009246556 2019-01-18 21:50:45 Acre 0.0014674090 2019-01-18 21:50:45 Amazonas 0.0008076088 2019-01-18 21:50:45 Roraima 0.0019616397 2019-01-18 21:50:45 Para 0.0005560644 2019-01-18 21:50:45 Amapa 0.0015394051 2019-01-18 21:50:45 Tocantins 0.0007904260 2019-01-18 21:50:45 Maranhao 0.0005031827 2019-01-18 21:50:45 Piaui 0.0008290869 2019-01-18 21:50:45 Ceara 0.0004497972 2019-01-18 21:50:45 Rio Grande do Norte 0.0008851713 2019-01-18 21:50:45 Paraiba 0.0006584047 2019-01-18 21:50:45 Pernambuco 0.0004462012 2019-01-18 21:50:45 Alagoas 0.0008115701 2019-01-18 21:50:45 Sergipe 0.0009918646 2019-01-18 21:50:45 Bahia 0.0003474925 2019-01-18 21:50:45 Minas Gerais 0.0003056574 2019-01-18 21:50:45 Espirito Santo 0.0006574212 2019-01-18 21:50:45 Rio de Janeiro 0.0004261408 2019-01-18 21:50:45 Sao Paulo 0.0002162530 2019-01-18 21:50:45 Parana 0.0003264035 2019-01-18 21:50:45 Santa Catarina 0.0004534673 2019-01-18 21:50:45 Rio Grande do Sul 0.0003719678 2019-01-18 21:50:45 Mato Grosso do Sul 0.0009235700 2019-01-18 21:50:45 Mato Grosso 0.0007216342 2019-01-18 21:50:45 Goias 0.0005157195 2019-01-18 21:50:45 Distrito Federal 0.0011208914 2019-01-18 21:50:45 2019-01-18 21:50:45 > svytotal(~v6033, censo_design) 2019-01-18 21:50:45 QQ: 'SELECT 1' 2019-01-18 21:50:45 II: Finished in 0s 2019-01-18 21:50:45 QQ: 'select v6033 from c10' 2019-01-18 21:50:45 II: Finished in 0s 2019-01-18 21:51:02 total SE 2019-01-18 21:51:02 v6033 8494688084 6201562 2019-01-18 21:51:02 2019-01-18 21:51:02 > svyby(~v6033, ~state_name, censo_design, svytotal) 2019-01-18 21:51:02 QQ: 'SELECT 1' 2019-01-18 21:51:02 II: Finished in 0s 2019-01-18 21:51:02 QQ: 'select v6033 from c10' 2019-01-18 21:51:02 II: Finished in 0s 2019-01-18 21:51:02 QQ: 'SELECT 1' 2019-01-18 21:51:02 II: Finished in 0s 2019-01-18 21:51:02 QQ: 'select v0001 from c10' 2019-01-18 21:51:02 II: Finished in 0.14s 2019-01-18 21:54:45 state_name v6033 se 2019-01-18 21:54:45 Rondonia Rondonia 67927439 509181.5 2019-01-18 21:54:45 Acre Acre 32383247 344246.3 2019-01-18 21:54:45 Amazonas Amazonas 156406314 1060384.8 2019-01-18 21:54:45 Roraima Roraima 20096387 248052.6 2019-01-18 21:54:45 Para Para 334081201 1210250.9 2019-01-18 21:54:45 Amapa Amapa 29702659 358844.1 2019-01-18 21:54:45 Tocantins Tocantins 60993702 375053.5 2019-01-18 21:54:45 Maranhao Maranhao 291865565 1043775.9 2019-01-18 21:54:45 Piaui Piaui 137950175 694189.2 2019-01-18 21:54:45 Ceara Ceara 371667509 1207529.6 2019-01-18 21:54:45 Rio Grande do Norte Rio Grande do Norte 139571251 655278.3 2019-01-18 21:54:45 Paraiba Paraiba 171031139 695481.2 2019-01-18 21:54:45 Pernambuco Pernambuco 390167775 1208391.2 2019-01-18 21:54:45 Alagoas Alagoas 138520597 722484.5 2019-01-18 21:54:45 Sergipe Sergipe 90310670 565908.5 2019-01-18 21:54:45 Bahia Bahia 616752560 1388099.0 2019-01-18 21:54:45 Minas Gerais Minas Gerais 866719202 1671802.1 2019-01-18 21:54:45 Espirito Santo Espirito Santo 156171746 675775.5 2019-01-18 21:54:45 Rio de Janeiro Rio de Janeiro 721390292 1481991.5 2019-01-18 21:54:45 Sao Paulo Sao Paulo 1851082734 2734891.5 2019-01-18 21:54:45 Parana Parana 468793290 1166754.4 2019-01-18 21:54:45 Santa Catarina Santa Catarina 277580763 733320.0 2019-01-18 21:54:45 Rio Grande do Sul Rio Grande do Sul 483239360 1201743.1 2019-01-18 21:54:45 Mato Grosso do Sul Mato Grosso do Sul 110416076 583800.7 2019-01-18 21:54:45 Mato Grosso Mato Grosso 132644212 783451.6 2019-01-18 21:54:45 Goias Goias 265134506 973504.7 2019-01-18 21:54:45 Distrito Federal Distrito Federal 112087713 756390.2 2019-01-18 21:54:45 2019-01-18 21:54:45 > svytotal(~sexo, censo_design) 2019-01-18 21:54:45 QQ: 'SELECT 1' 2019-01-18 21:56:04 II: Finished in 1.32s 2019-01-18 21:56:04 QQ: 'select v0601 from c10' 2019-01-18 21:56:04 II: Finished in 0.15s 2019-01-18 21:56:31 total SE 2019-01-18 21:56:31 sexomasculino 93406990 31068 2019-01-18 21:56:31 sexofeminino 97348809 34764 2019-01-18 21:56:31 2019-01-18 21:56:31 > svyby(~sexo, ~state_name, censo_design, svytotal) 2019-01-18 21:56:31 QQ: 'SELECT 1' 2019-01-18 21:56:31 II: Finished in 0s 2019-01-18 21:56:31 QQ: 'select v0601 from c10' 2019-01-18 21:56:31 II: Finished in 0.14s 2019-01-18 21:56:33 QQ: 'SELECT 1' 2019-01-18 21:56:33 II: Finished in 0s 2019-01-18 21:56:33 QQ: 'select v0001 from c10' 2019-01-18 21:56:33 II: Finished in 0.18s 2019-01-18 22:00:30 state_name sexomasculino sexofeminino se1 2019-01-18 22:00:30 Rondonia Rondonia 795157 767252 2634.502 2019-01-18 22:00:30 Acre Acre 368324 365235 1816.293 2019-01-18 22:00:30 Amazonas Amazonas 1753179 1730806 5904.954 2019-01-18 22:00:30 Roraima Roraima 228859 221620 1410.254 2019-01-18 22:00:30 Para Para 3821837 3759214 7325.971 2019-01-18 22:00:30 Amapa Amapa 335135 334391 2172.839 2019-01-18 22:00:30 Tocantins Tocantins 702424 681021 1984.120 2019-01-18 22:00:30 Maranhao Maranhao 3261515 3313274 5617.714 2019-01-18 22:00:30 Piaui Piaui 1528422 1589938 3703.228 2019-01-18 22:00:30 Ceara Ceara 4120088 4332293 6651.846 2019-01-18 22:00:30 Rio Grande do Norte Rio Grande do Norte 1548887 1619140 4107.783 2019-01-18 22:00:30 Paraiba Paraiba 1824379 1942149 3789.801 2019-01-18 22:00:30 Pernambuco Pernambuco 4230681 4565767 6466.627 2019-01-18 22:00:30 Alagoas Alagoas 1511767 1608727 4250.715 2019-01-18 22:00:30 Sergipe Sergipe 1005041 1062976 3009.760 2019-01-18 22:00:30 Bahia Bahia 6878266 7138640 7227.692 2019-01-18 22:00:30 Minas Gerais Minas Gerais 9641877 9955453 8954.524 2019-01-18 22:00:30 Espirito Santo Espirito Santo 1731218 1783734 3415.531 2019-01-18 22:00:30 Rio de Janeiro Rio de Janeiro 7625679 8364250 10443.419 2019-01-18 22:00:30 Sao Paulo Sao Paulo 20077873 21184326 14556.894 2019-01-18 22:00:30 Parana Parana 5130994 5313532 5388.981 2019-01-18 22:00:30 Santa Catarina Santa Catarina 3100360 3148076 3947.547 2019-01-18 22:00:30 Rio Grande do Sul Rio Grande do Sul 5205057 5488872 7038.359 2019-01-18 22:00:30 Mato Grosso do Sul Mato Grosso do Sul 1219928 1229096 3262.749 2019-01-18 22:00:30 Mato Grosso Mato Grosso 1549536 1485586 3835.780 2019-01-18 22:00:30 Goias Goias 2981627 3022161 5784.797 2019-01-18 22:00:30 Distrito Federal Distrito Federal 1228880 1341280 4960.455 2019-01-18 22:00:30 se2 2019-01-18 22:00:30 Rondonia 2251.113 2019-01-18 22:00:30 Acre 1707.873 2019-01-18 22:00:30 Amazonas 4845.495 2019-01-18 22:00:30 Roraima 1534.237 2019-01-18 22:00:30 Para 7891.117 2019-01-18 22:00:30 Amapa 1926.803 2019-01-18 22:00:30 Tocantins 2157.595 2019-01-18 22:00:30 Maranhao 5699.299 2019-01-18 22:00:30 Piaui 3685.326 2019-01-18 22:00:30 Ceara 6747.733 2019-01-18 22:00:30 Rio Grande do Norte 4177.838 2019-01-18 22:00:30 Paraiba 4138.700 2019-01-18 22:00:30 Pernambuco 6656.523 2019-01-18 22:00:30 Alagoas 4590.469 2019-01-18 22:00:30 Sergipe 3293.426 2019-01-18 22:00:30 Bahia 8745.274 2019-01-18 22:00:30 Minas Gerais 10178.023 2019-01-18 22:00:30 Espirito Santo 3612.557 2019-01-18 22:00:30 Rio de Janeiro 10089.562 2019-01-18 22:00:30 Sao Paulo 14476.726 2019-01-18 22:00:30 Parana 6637.420 2019-01-18 22:00:30 Santa Catarina 4338.580 2019-01-18 22:00:30 Rio Grande do Sul 6645.932 2019-01-18 22:00:30 Mato Grosso do Sul 3474.413 2019-01-18 22:00:30 Mato Grosso 4159.713 2019-01-18 22:00:30 Goias 4769.577 2019-01-18 22:00:30 Distrito Federal 4510.593 2019-01-18 22:00:30 2019-01-18 22:00:30 > svyquantile(~v6033, censo_design, 0.5) 2019-01-18 22:00:30 QQ: 'SELECT 1' 2019-01-18 22:00:30 II: Finished in 0s 2019-01-18 22:00:30 QQ: 'select v6033 from c10' 2019-01-18 22:00:30 II: Finished in 0s 2019-01-18 22:01:09 QQ: 'SELECT 1' 2019-01-18 22:01:28 II: Finished in 18.81s 2019-01-18 22:02:13 Statistic: 2019-01-18 22:02:13 v6033 2019-01-18 22:02:13 q0.5 30 2019-01-18 22:02:13 SE: 2019-01-18 22:02:13 v6033 2019-01-18 22:02:13 q0.5 0.25 2019-01-18 22:02:13 2019-01-18 22:02:13 > svyby(~v6033, ~state_name, censo_design, svyquantile, 2019-01-18 22:02:13 + 0.5, ci = TRUE, keep.var = TRUE) 2019-01-18 22:02:13 QQ: 'SELECT 1' 2019-01-18 22:02:13 II: Finished in 0s 2019-01-18 22:02:13 QQ: 'select v6033 from c10' 2019-01-18 22:02:13 II: Finished in 0s 2019-01-18 22:02:13 QQ: 'SELECT 1' 2019-01-18 22:02:13 II: Finished in 0s 2019-01-18 22:02:13 QQ: 'select v0001 from c10' 2019-01-18 22:02:13 II: Finished in 0.19s 2019-01-18 22:06:29 state_name V1 se 2019-01-18 22:06:29 Rondonia Rondonia 27 0.25 2019-01-18 22:06:29 Acre Acre 24 0.25 2019-01-18 22:06:29 Amazonas Amazonas 24 0.25 2019-01-18 22:06:29 Roraima Roraima 24 0.25 2019-01-18 22:06:29 Para Para 25 0.25 2019-01-18 22:06:29 Amapa Amapa 23 0.25 2019-01-18 22:06:29 Tocantins Tocantins 26 0.25 2019-01-18 22:06:29 Maranhao Maranhao 25 0.25 2019-01-18 22:06:29 Piaui Piaui 28 0.25 2019-01-18 22:06:29 Ceara Ceara 28 0.25 2019-01-18 22:06:29 Rio Grande do Norte Rio Grande do Norte 29 0.25 2019-01-18 22:06:29 Paraiba Paraiba 29 0.25 2019-01-18 22:06:29 Pernambuco Pernambuco 29 0.25 2019-01-18 22:06:29 Alagoas Alagoas 26 0.25 2019-01-18 22:06:29 Sergipe Sergipe 27 0.25 2019-01-18 22:06:29 Bahia Bahia 28 0.25 2019-01-18 22:06:29 Minas Gerais Minas Gerais 31 0.25 2019-01-18 22:06:29 Espirito Santo Espirito Santo 30 0.25 2019-01-18 22:06:29 Rio de Janeiro Rio de Janeiro 33 0.25 2019-01-18 22:06:29 Sao Paulo Sao Paulo 32 0.25 2019-01-18 22:06:29 Parana Parana 31 0.25 2019-01-18 22:06:29 Santa Catarina Santa Catarina 31 0.25 2019-01-18 22:06:29 Rio Grande do Sul Rio Grande do Sul 33 0.25 2019-01-18 22:06:29 Mato Grosso do Sul Mato Grosso do Sul 29 0.25 2019-01-18 22:06:29 Mato Grosso Mato Grosso 28 0.25 2019-01-18 22:06:29 Goias Goias 30 0.25 2019-01-18 22:06:29 Distrito Federal Distrito Federal 29 0.25 2019-01-18 22:06:29 2019-01-18 22:06:29 > svyratio(numerator = ~nmorpob1, denominator = ~nmorpob1 + 2019-01-18 22:06:29 + one, censo_design, na.rm = TRUE) 2019-01-18 22:06:29 QQ: 'SELECT 1' 2019-01-18 22:08:16 II: Finished in 1.79s 2019-01-18 22:08:16 QQ: 'select v6531 from c10' 2019-01-18 22:08:36 II: Finished in 19.58s 2019-01-18 22:08:37 QQ: 'SELECT 1' 2019-01-18 22:08:37 II: Finished in 0s 2019-01-18 22:08:37 QQ: 'select one, v6531 from c10' 2019-01-18 22:08:37 II: Finished in 0.05s 2019-01-18 22:13:32 QQ: 'SELECT 1' 2019-01-18 22:13:52 II: Finished in 20.01s 2019-01-18 22:15:00 Ratio estimator: svyratio.svyrep.design(numerator = ~nmorpob1, denominator = ~nmorpob1 + 2019-01-18 22:15:00 one, censo_design, na.rm = TRUE) 2019-01-18 22:15:00 Ratios= 2019-01-18 22:15:00 nmorpob1 one 2019-01-18 22:15:00 nmorpob1 1 0.09317731 2019-01-18 22:15:00 SEs= 2019-01-18 22:15:00 [,1] [,2] 2019-01-18 22:15:00 [1,] 0 0.0001517815 2019-01-18 22:15:00 2019-01-18 22:15:00 > sub_censo_design <- subset(censo_design, v0640 == 2019-01-18 22:15:00 + 1) 2019-01-18 22:15:00 QQ: 'SELECT 1' 2019-01-18 22:15:55 II: Finished in 54.73s 2019-01-18 22:15:55 QQ: 'select v0640 from c10' 2019-01-18 22:15:56 II: Finished in 1.27s 2019-01-18 22:16:59 2019-01-18 22:16:59 > svymean(~v6033, sub_censo_design) 2019-01-18 22:16:59 QQ: 'SELECT 1' 2019-01-18 22:17:57 II: Finished in 58.22s 2019-01-18 22:17:57 QQ: 'select v6033 from c10' 2019-01-18 22:17:57 II: Finished in 0s 2019-01-18 22:18:15 mean SE 2019-01-18 22:18:15 v6033 45.922 0.0079 2019-01-18 22:18:15 2019-01-18 22:18:15 > this_result <- svymean(~v6033, censo_design) 2019-01-18 22:18:15 QQ: 'SELECT 1' 2019-01-18 22:18:15 II: Finished in 0s 2019-01-18 22:18:15 QQ: 'select v6033 from c10' 2019-01-18 22:18:15 II: Finished in 0s 2019-01-18 22:18:54 2019-01-18 22:18:54 > coef(this_result) 2019-01-18 22:18:54 v6033 2019-01-18 22:18:54 44.53174 2019-01-18 22:18:54 2019-01-18 22:18:54 > SE(this_result) 2019-01-18 22:18:54 [1] 0.02908 2019-01-18 22:18:54 2019-01-18 22:18:54 > confint(this_result) 2019-01-18 22:18:54 2.5 % 97.5 % 2019-01-18 22:18:54 v6033 44.47475 44.58874 2019-01-18 22:18:54 2019-01-18 22:18:54 > cv(this_result) 2019-01-18 22:18:54 v6033 2019-01-18 22:18:54 0.0006530174 2019-01-18 22:18:54 2019-01-18 22:18:54 > grouped_result <- svyby(~v6033, ~state_name, censo_design, 2019-01-18 22:18:54 + svymean) 2019-01-18 22:18:54 QQ: 'SELECT 1' 2019-01-18 22:19:09 II: Finished in 14.97s 2019-01-18 22:19:10 QQ: 'select v6033 from c10' 2019-01-18 22:19:10 II: Finished in 0s 2019-01-18 22:19:10 QQ: 'SELECT 1' 2019-01-18 22:19:10 II: Finished in 0s 2019-01-18 22:19:10 QQ: 'select v0001 from c10' 2019-01-18 22:19:10 II: Finished in 0.25s 2019-01-18 22:23:09 2019-01-18 22:23:09 > coef(grouped_result) 2019-01-18 22:23:09 Rondonia Acre Amazonas Roraima 2019-01-18 22:23:09 43.47609 44.14539 44.89294 44.61115 2019-01-18 22:23:09 Para Amapa Tocantins Maranhao 2019-01-18 22:23:09 44.06793 44.36371 44.08827 44.39162 2019-01-18 22:23:09 Piaui Ceara Rio Grande do Norte Paraiba 2019-01-18 22:23:09 44.23805 43.97193 44.05621 45.40817 2019-01-18 22:23:09 Pernambuco Alagoas Sergipe Bahia 2019-01-18 22:23:09 44.35515 44.39060 43.67018 44.00062 2019-01-18 22:23:09 Minas Gerais Espirito Santo Rio de Janeiro Sao Paulo 2019-01-18 22:23:09 44.22639 44.43069 45.11529 44.86147 2019-01-18 22:23:09 Parana Santa Catarina Rio Grande do Sul Mato Grosso do Sul 2019-01-18 22:23:09 44.88411 44.42404 45.18820 45.08575 2019-01-18 22:23:09 Mato Grosso Goias Distrito Federal 2019-01-18 22:23:09 43.70309 44.16120 43.61118 2019-01-18 22:23:09 2019-01-18 22:23:09 > SE(grouped_result) 2019-01-18 22:23:09 [1] 0.29255813 0.42900430 0.26248045 0.48059649 0.12801155 0.47275275 2019-01-18 22:23:09 [7] 0.24578628 0.14799628 0.20966135 0.12519040 0.18677314 0.17778339 2019-01-18 22:23:09 [13] 0.12297141 0.21888708 0.26465445 0.09072600 0.07945220 0.18252646 2019-01-18 22:23:09 [19] 0.08475508 0.06044199 0.11843766 0.11024326 0.10302228 0.22239028 2019-01-18 22:23:09 [25] 0.22561486 0.15141651 0.29819552 2019-01-18 22:23:09 2019-01-18 22:23:09 > confint(grouped_result) 2019-01-18 22:23:09 2.5 % 97.5 % 2019-01-18 22:23:09 Rondonia 42.90269 44.04950 2019-01-18 22:23:09 Acre 43.30456 44.98622 2019-01-18 22:23:09 Amazonas 44.37848 45.40739 2019-01-18 22:23:09 Roraima 43.66920 45.55310 2019-01-18 22:23:09 Para 43.81703 44.31882 2019-01-18 22:23:09 Amapa 43.43713 45.29029 2019-01-18 22:23:09 Tocantins 43.60654 44.57001 2019-01-18 22:23:09 Maranhao 44.10156 44.68169 2019-01-18 22:23:09 Piaui 43.82712 44.64898 2019-01-18 22:23:09 Ceara 43.72656 44.21730 2019-01-18 22:23:09 Rio Grande do Norte 43.69014 44.42227 2019-01-18 22:23:09 Paraiba 45.05972 45.75662 2019-01-18 22:23:09 Pernambuco 44.11413 44.59617 2019-01-18 22:23:09 Alagoas 43.96159 44.81961 2019-01-18 22:23:09 Sergipe 43.15146 44.18889 2019-01-18 22:23:09 Bahia 43.82280 44.17844 2019-01-18 22:23:09 Minas Gerais 44.07067 44.38212 2019-01-18 22:23:09 Espirito Santo 44.07295 44.78844 2019-01-18 22:23:09 Rio de Janeiro 44.94917 45.28141 2019-01-18 22:23:09 Sao Paulo 44.74300 44.97993 2019-01-18 22:23:09 Parana 44.65198 45.11625 2019-01-18 22:23:09 Santa Catarina 44.20797 44.64011 2019-01-18 22:23:09 Rio Grande do Sul 44.98628 45.39012 2019-01-18 22:23:09 Mato Grosso do Sul 44.64987 45.52162 2019-01-18 22:23:09 Mato Grosso 43.26089 44.14529 2019-01-18 22:23:09 Goias 43.86443 44.45797 2019-01-18 22:23:09 Distrito Federal 43.02673 44.19563 2019-01-18 22:23:09 2019-01-18 22:23:09 > cv(grouped_result) 2019-01-18 22:23:09 Rondonia Acre Amazonas Roraima 2019-01-18 22:23:09 0.006729172 0.009717987 0.005846810 0.010773012 2019-01-18 22:23:09 Para Amapa Tocantins Maranhao 2019-01-18 22:23:09 0.002904869 0.010656294 0.005574867 0.003333878 2019-01-18 22:23:09 Piaui Ceara Rio Grande do Norte Paraiba 2019-01-18 22:23:09 0.004739389 0.002847053 0.004239429 0.003915229 2019-01-18 22:23:09 Pernambuco Alagoas Sergipe Bahia 2019-01-18 22:23:09 0.002772427 0.004930933 0.006060302 0.002061925 2019-01-18 22:23:09 Minas Gerais Espirito Santo Rio de Janeiro Sao Paulo 2019-01-18 22:23:09 0.001796488 0.004108117 0.001878633 0.001347303 2019-01-18 22:23:09 Parana Santa Catarina Rio Grande do Sul Mato Grosso do Sul 2019-01-18 22:23:09 0.002638744 0.002481613 0.002279849 0.004932607 2019-01-18 22:23:09 Mato Grosso Goias Distrito Federal 2019-01-18 22:23:09 0.005162446 0.003428722 0.006837593 2019-01-18 22:23:09 2019-01-18 22:23:09 > degf(censo_design) 2019-01-18 22:23:09 [1] 79 2019-01-18 22:23:09 2019-01-18 22:23:09 > svyvar(~v6033, censo_design) 2019-01-18 22:23:09 QQ: 'SELECT 1' 2019-01-18 22:23:37 II: Finished in 28.44s 2019-01-18 22:23:38 QQ: 'select v6033 from c10' 2019-01-18 22:23:38 II: Finished in 0s 2019-01-18 22:25:08 variance SE 2019-01-18 22:25:08 v6033 11161 24.622 2019-01-18 22:25:08 2019-01-18 22:25:08 > svymean(~v6033, censo_design, deff = TRUE) 2019-01-18 22:25:08 QQ: 'SELECT 1' 2019-01-18 22:26:07 II: Finished in 59.55s 2019-01-18 22:26:07 QQ: 'select v6033 from c10' 2019-01-18 22:26:07 II: Finished in 0.26s 2019-01-18 22:26:35 QQ: 'SELECT 1' 2019-01-18 22:26:36 II: Finished in 0s 2019-01-18 22:26:36 mean SE DEff 2019-01-18 22:26:36 v6033 44.53174 0.02908 1.7531 2019-01-18 22:26:36 2019-01-18 22:26:36 > svymean(~v6033, censo_design, deff = "replace") 2019-01-18 22:26:36 QQ: 'SELECT 1' 2019-01-18 22:26:36 II: Finished in 0s 2019-01-18 22:26:36 QQ: 'select v6033 from c10' 2019-01-18 22:26:36 II: Finished in 0s 2019-01-18 22:27:00 QQ: 'SELECT 1' 2019-01-18 22:28:20 II: Finished in 1.34s 2019-01-18 22:28:21 mean SE DEff 2019-01-18 22:28:21 v6033 44.53174 0.02908 1.5635 2019-01-18 22:28:21 2019-01-18 22:28:21 > svyciprop(~nmorpob6, censo_design, method = "likelihood", 2019-01-18 22:28:21 + na.rm = TRUE) 2019-01-18 22:28:42 QQ: 'SELECT 1' 2019-01-18 22:28:42 II: Finished in 0s 2019-01-18 22:28:42 QQ: 'select v6531 from c10' 2019-01-18 22:28:42 II: Finished in 0.06s 2019-01-18 22:57:36 QQ: 'SELECT 1' 2019-01-18 22:57:36 II: Finished in 0.02s 2019-01-18 22:57:36 QQ: 'select v6531 from c10' 2019-01-18 22:57:36 II: Finished in 0.05s 2019-01-18 23:01:37 2.5% 97.5% 2019-01-18 23:01:37 nmorpob6 0.365 NA NA 2019-01-18 23:01:37 2019-01-18 23:01:37 > svyttest(v6033 ~ nmorpob6, censo_design) 2019-01-18 23:01:59 QQ: 'SELECT 1' 2019-01-18 23:01:59 II: Finished in 0s 2019-01-18 23:01:59 QQ: 'select v6033, v6531 from c10' 2019-01-18 23:01:59 II: Finished in 0.05s 2019-01-18 23:26:13 2019-01-18 23:26:13 Design-based t-test 2019-01-18 23:26:13 2019-01-18 23:26:13 data: v6033 ~ nmorpob6 2019-01-18 23:26:13 t = 8.9048, df = 78, p-value = 1.651e-13 2019-01-18 23:26:13 alternative hypothesis: true difference in mean is not equal to 0 2019-01-18 23:26:13 95 percent confidence interval: 2019-01-18 23:26:13 0.4484612 0.7015879 2019-01-18 23:26:13 sample estimates: 2019-01-18 23:26:13 difference in mean 2019-01-18 23:26:13 0.5750246 2019-01-18 23:26:13 2019-01-18 23:26:13 2019-01-18 23:26:13 > svychisq(~nmorpob6 + sexo, censo_design) 2019-01-18 23:26:13 QQ: 'SELECT 1' 2019-01-18 23:26:54 II: Finished in 41.37s 2019-01-18 23:26:54 QQ: 'select v6531, v0601 from c10' 2019-01-18 23:26:54 II: Finished in 0.28s 2019-01-18 23:27:12 QQ: 'SELECT 1' 2019-01-18 23:27:12 II: Finished in 0s 2019-01-18 23:27:12 QQ: 'select v6531, v0601 from c10' 2019-01-18 23:27:12 II: Finished in 0.22s 2019-01-18 23:27:31 QQ: 'SELECT 1' 2019-01-18 23:27:31 II: Finished in 0s 2019-01-18 23:32:04 QQ: 'SELECT 1' 2019-01-18 23:32:37 II: Finished in 33.25s 2019-01-18 23:32:37 QQ: 'select v6531, v0601 from c10' 2019-01-18 23:32:38 II: Finished in 0.35s 2019-01-18 23:33:01 2019-01-18 23:33:01 Pearson's X^2: Rao & Scott adjustment 2019-01-18 23:33:01 2019-01-18 23:33:01 data: NextMethod("svychisq", design) 2019-01-18 23:33:01 F = 227.6, ndf = 1, ddf = 79, p-value < 2.2e-16 2019-01-18 23:33:01 2019-01-18 23:33:01 2019-01-18 23:33:01 > glm_result <- svyglm(v6033 ~ nmorpob6 + sexo, censo_design) 2019-01-18 23:33:22 QQ: 'SELECT 1' 2019-01-18 23:33:22 II: Finished in 0s 2019-01-18 23:33:22 QQ: 'select v6033, v6531, v0601 from c10' 2019-01-18 23:33:22 II: Finished in 0.22s 2019-01-18 23:59:14 2019-01-18 23:59:14 > summary(glm_result) 2019-01-18 23:59:19 2019-01-18 23:59:19 Call: 2019-01-18 23:59:19 NextMethod(formula = "svyglm", design) 2019-01-18 23:59:19 2019-01-18 23:59:19 Survey design: 2019-01-18 23:59:19 survey::svrepdesign(weight = as.formula(paste0("~", unique_designs[i, 2019-01-18 23:59:19 "type"], "_wgt")), repweights = bootw$repweights, type = "bootstrap", 2019-01-18 23:59:19 combined.weights = FALSE, scale = bootw$scale, rscales = bootw$rscales, 2019-01-18 23:59:19 data = paste0("c", substr(unique_designs[i, "year"], 3, 4), 2019-01-18 23:59:19 ifelse(unique_designs[i, "type"] == "pes", "", paste0("_", 2019-01-18 23:59:19 unique_designs[i, "type"]))), dbtype = "MonetDBLite", 2019-01-18 23:59:19 dbname = unique_designs[i, "dbfolder"]) 2019-01-18 23:59:19 2019-01-18 23:59:19 Coefficients: 2019-01-18 23:59:19 Estimate Std. Error t value Pr(>|t|) 2019-01-18 23:59:19 (Intercept) 44.06560 0.04081 1079.698 <2e-16 *** 2019-01-18 23:59:19 nmorpob6 0.57361 0.06456 8.884 2e-13 *** 2019-01-18 23:59:19 sexofeminino 0.51847 0.04950 10.475 <2e-16 *** 2019-01-18 23:59:19 --- 2019-01-18 23:59:19 Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 2019-01-18 23:59:19 2019-01-18 23:59:19 (Dispersion parameter for gaussian family taken to be 230099349638) 2019-01-18 23:59:19 2019-01-18 23:59:19 Number of Fisher Scoring iterations: 2 2019-01-18 23:59:19 2019-01-18 23:59:19 2019-01-18 23:59:19 > library(convey) 2019-01-18 23:59:20 2019-01-18 23:59:20 > censo_design <- convey_prep(censo_design) 2019-01-18 23:59:20 2019-01-18 23:59:20 > sub_censo_design <- subset(censo_design, v6531 >= 2019-01-18 23:59:20 + 0) 2019-01-18 23:59:20 QQ: 'SELECT 1' 2019-01-18 23:59:20 II: Finished in 0.1s 2019-01-18 23:59:20 QQ: 'select v6531 from c10' 2019-01-18 23:59:20 II: Finished in 0.08s 2019-01-19 00:02:46 2019-01-19 00:02:46 > svygini(~v6531, sub_censo_design, na.rm = TRUE) 2019-01-19 00:02:46 QQ: 'SELECT 1' 2019-01-19 00:02:46 II: Finished in 0s 2019-01-19 00:02:46 QQ: 'select v6531 from c10' 2019-01-19 00:02:47 II: Finished in 0.08s 2019-01-19 00:02:47 QQ: 'SELECT 1' 2019-01-19 00:02:47 II: Finished in 0s 2019-01-19 00:02:47 QQ: 'select v6531 from c10' 2019-01-19 00:02:47 II: Finished in 0.06s 2019-01-19 00:12:21 gini SE 2019-01-19 00:12:21 v6531 0.61061 7e-04 2019-01-19 00:12:21 2019-01-19 00:12:21 > close(censo_design, shutdown = TRUE) 2019-01-19 00:12:27 > test return code=0