2019-02-10 05:42:47 2019-02-10 05:42:47 R version 3.5.1 (2018-07-02) -- "Feather Spray" 2019-02-10 05:42:47 Copyright (C) 2018 The R Foundation for Statistical Computing 2019-02-10 05:42:47 Platform: x86_64-pc-linux-gnu (64-bit) 2019-02-10 05:42:47 2019-02-10 05:42:47 R is free software and comes with ABSOLUTELY NO WARRANTY. 2019-02-10 05:42:47 You are welcome to redistribute it under certain conditions. 2019-02-10 05:42:47 Type 'license()' or 'licence()' for distribution details. 2019-02-10 05:42:47 2019-02-10 05:42:47 Natural language support but running in an English locale 2019-02-10 05:42:47 2019-02-10 05:42:47 R is a collaborative project with many contributors. 2019-02-10 05:42:47 Type 'contributors()' for more information and 2019-02-10 05:42:47 'citation()' on how to cite R or R packages in publications. 2019-02-10 05:42:47 2019-02-10 05:42:47 Type 'demo()' for some demos, 'help()' for on-line help, or 2019-02-10 05:42:47 'help.start()' for an HTML browser interface to help. 2019-02-10 05:42:47 Type 'q()' to quit R. 2019-02-10 05:42:47 2019-02-10 05:42:47 > setwd( Sys.getenv( "RWD" ) ) 2019-02-10 05:42:47 > a <- lodown::get_catalog("censo") 2019-02-10 05:42:47 building catalog for censo 2019-02-10 05:42:47 2019-02-10 05:42:53 > # don't do 2000 it's been broken forever 2019-02-10 05:42:53 > lodown::lodown("censo", catalog=a[a$year == 2010,], output_dir= getwd()) 2019-02-10 05:42:53 locally downloading censo 2019-02-10 05:42:53 2019-02-10 05:42:56 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/AC.zip' 2019-02-10 05:42:56 cached in 2019-02-10 05:42:56 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/8d33c41dcfde91034b1afbc3105bd061.Rcache' 2019-02-10 05:42:56 copying to 2019-02-10 05:42:56 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpitRJKD/file5557af1cac4' 2019-02-10 05:42:56 2019-02-10 05:43:06 censo catalog entry 1 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755/MonetDB' 2019-02-10 05:43:06 2019-02-10 05:47:34 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/AL.zip' 2019-02-10 05:47:34 cached in 2019-02-10 05:47:34 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/675d0405924a1b73a6f889f953a759ab.Rcache' 2019-02-10 05:47:34 copying to 2019-02-10 05:47:34 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpitRJKD/file5557af1cac4' 2019-02-10 05:47:34 2019-02-10 05:50:52 censo catalog entry 2 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755/MonetDB' 2019-02-10 05:50:52 2019-02-10 05:58:40 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/AM.zip' 2019-02-10 05:58:40 cached in 2019-02-10 05:58:40 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/8a1e7a9111551585f7cec0b7b767e0c7.Rcache' 2019-02-10 05:58:40 copying to 2019-02-10 05:58:40 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpitRJKD/file5557af1cac4' 2019-02-10 05:58:40 2019-02-10 06:03:26 censo catalog entry 3 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755/MonetDB' 2019-02-10 06:03:26 2019-02-10 06:06:28 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/AP.zip' 2019-02-10 06:06:28 cached in 2019-02-10 06:06:28 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/6eeff2ce0144bb14d5a56c6ca27fcdf9.Rcache' 2019-02-10 06:06:28 copying to 2019-02-10 06:06:28 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpitRJKD/file5557af1cac4' 2019-02-10 06:06:28 2019-02-10 06:08:45 censo catalog entry 4 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755/MonetDB' 2019-02-10 06:08:45 2019-02-10 06:51:12 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/BA.zip' 2019-02-10 06:51:12 cached in 2019-02-10 06:51:12 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/f12488e852651d05e153bb9f21b670ed.Rcache' 2019-02-10 06:51:12 copying to 2019-02-10 06:51:12 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpitRJKD/file5557af1cac4' 2019-02-10 06:51:12 2019-02-10 07:03:39 censo catalog entry 5 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755/MonetDB' 2019-02-10 07:03:39 2019-02-10 07:08:06 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/CE.zip' 2019-02-10 07:08:06 cached in 2019-02-10 07:08:06 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/6e5d97ea080321a3f736da278ccb0c36.Rcache' 2019-02-10 07:08:06 copying to 2019-02-10 07:08:06 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpitRJKD/file5557af1cac4' 2019-02-10 07:08:06 2019-02-10 07:18:43 censo catalog entry 6 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755/MonetDB' 2019-02-10 07:18:43 2019-02-10 07:19:00 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/DF.zip' 2019-02-10 07:19:00 cached in 2019-02-10 07:19:00 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/31c64b57fe5442cb7c07b351e8c5a51c.Rcache' 2019-02-10 07:19:00 copying to 2019-02-10 07:19:00 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpitRJKD/file5557af1cac4' 2019-02-10 07:19:00 2019-02-10 07:19:50 censo catalog entry 7 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755/MonetDB' 2019-02-10 07:19:50 2019-02-10 07:48:22 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/ES.zip' 2019-02-10 07:48:22 cached in 2019-02-10 07:48:22 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/b751b8a9e5ee7aa58c52b86c25bd041e.Rcache' 2019-02-10 07:48:22 copying to 2019-02-10 07:48:22 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpitRJKD/file5557af1cac4' 2019-02-10 07:48:22 2019-02-10 08:55:26 censo catalog entry 8 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755/MonetDB' 2019-02-10 08:55:26 2019-02-10 09:58:26 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/GO.zip' 2019-02-10 09:58:27 cached in 2019-02-10 09:58:27 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/f29a3850a4b737df7e2e8ea62f0007b9.Rcache' 2019-02-10 09:58:27 copying to 2019-02-10 09:58:27 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpitRJKD/file5557af1cac4' 2019-02-10 09:58:27 2019-02-10 10:03:06 censo catalog entry 9 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755/MonetDB' 2019-02-10 10:03:06 2019-02-10 10:04:22 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/MA.zip' 2019-02-10 10:04:22 cached in 2019-02-10 10:04:22 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/362a6e810463c8a0e38517f5163cc222.Rcache' 2019-02-10 10:04:22 copying to 2019-02-10 10:04:22 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpitRJKD/file5557af1cac4' 2019-02-10 10:04:22 2019-02-10 10:11:42 censo catalog entry 10 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755/MonetDB' 2019-02-10 10:11:42 2019-02-10 10:13:25 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/MG.zip' 2019-02-10 10:13:25 cached in 2019-02-10 10:13:25 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/90c71c4f917ad6d89d0f453c2e3c2dc9.Rcache' 2019-02-10 10:13:25 copying to 2019-02-10 10:13:25 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpitRJKD/file5557af1cac4' 2019-02-10 10:13:25 2019-02-10 10:23:33 censo catalog entry 11 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755/MonetDB' 2019-02-10 10:23:33 2019-02-10 10:28:24 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/MS.zip' 2019-02-10 10:28:24 cached in 2019-02-10 10:28:24 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/b5e5b1b9e2e979e74c9ec72feec10865.Rcache' 2019-02-10 10:28:24 copying to 2019-02-10 10:28:24 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpitRJKD/file5557af1cac4' 2019-02-10 10:28:24 2019-02-10 10:48:12 censo catalog entry 12 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755/MonetDB' 2019-02-10 10:48:12 2019-02-10 10:56:39 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/MT.zip' 2019-02-10 10:56:39 cached in 2019-02-10 10:56:39 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/86f0b09d2b55f9efa586af32e4f2314a.Rcache' 2019-02-10 10:56:39 copying to 2019-02-10 10:56:39 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpitRJKD/file5557af1cac4' 2019-02-10 10:56:39 2019-02-10 11:07:27 censo catalog entry 13 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755/MonetDB' 2019-02-10 11:07:27 2019-02-10 11:29:45 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/PA.zip' 2019-02-10 11:29:45 cached in 2019-02-10 11:29:45 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/738b3f4e5c93d2280a8b0a744134c648.Rcache' 2019-02-10 11:29:45 copying to 2019-02-10 11:29:45 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpitRJKD/file5557af1cac4' 2019-02-10 11:29:45 2019-02-10 11:52:53 censo catalog entry 14 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755/MonetDB' 2019-02-10 11:52:53 2019-02-10 12:00:21 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/PB.zip' 2019-02-10 12:00:21 cached in 2019-02-10 12:00:21 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/8bd47199975bdf2964c09aa4e21648e1.Rcache' 2019-02-10 12:00:21 copying to 2019-02-10 12:00:21 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpitRJKD/file5557af1cac4' 2019-02-10 12:00:21 2019-02-10 12:33:29 censo catalog entry 15 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755/MonetDB' 2019-02-10 12:33:29 2019-02-10 12:48:09 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/PE.zip' 2019-02-10 12:48:09 cached in 2019-02-10 12:48:09 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/eac1739962da73a00dfb693f03377c92.Rcache' 2019-02-10 12:48:09 copying to 2019-02-10 12:48:09 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpitRJKD/file5557af1cac4' 2019-02-10 12:48:09 2019-02-10 14:14:33 censo catalog entry 16 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755/MonetDB' 2019-02-10 14:14:34 2019-02-10 14:20:17 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/PI.zip' 2019-02-10 14:20:17 cached in 2019-02-10 14:20:17 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/06c1460710d6b2b70933afe955bf06ee.Rcache' 2019-02-10 14:20:17 copying to 2019-02-10 14:20:17 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpitRJKD/file5557af1cac4' 2019-02-10 14:20:17 2019-02-10 15:37:38 censo catalog entry 17 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755/MonetDB' 2019-02-10 15:37:38 2019-02-10 15:39:07 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/PR.zip' 2019-02-10 15:39:07 cached in 2019-02-10 15:39:07 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/409a9525b7a91b4618baf65cc89dce07.Rcache' 2019-02-10 15:39:07 copying to 2019-02-10 15:39:07 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpitRJKD/file5557af1cac4' 2019-02-10 15:39:07 2019-02-10 15:44:48 censo catalog entry 18 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755/MonetDB' 2019-02-10 15:44:48 2019-02-10 15:47:17 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/RJ.zip' 2019-02-10 15:47:17 cached in 2019-02-10 15:47:17 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/5b82d082ec19bfb478942334dee06362.Rcache' 2019-02-10 15:47:17 copying to 2019-02-10 15:47:17 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpitRJKD/file5557af1cac4' 2019-02-10 15:47:17 2019-02-10 15:51:26 censo catalog entry 19 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755/MonetDB' 2019-02-10 15:51:26 2019-02-10 15:52:32 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/RN.zip' 2019-02-10 15:52:32 cached in 2019-02-10 15:52:32 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/791786e4d34a82d9602a9782cfcf56ee.Rcache' 2019-02-10 15:52:32 copying to 2019-02-10 15:52:32 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpitRJKD/file5557af1cac4' 2019-02-10 15:52:32 2019-02-10 15:55:16 censo catalog entry 20 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755/MonetDB' 2019-02-10 15:55:16 2019-02-10 15:58:45 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/RO.zip' 2019-02-10 15:58:45 cached in 2019-02-10 15:58:45 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/d1e8db0e4c49bf7785e6765a73a0ef97.Rcache' 2019-02-10 15:58:45 copying to 2019-02-10 15:58:45 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpitRJKD/file5557af1cac4' 2019-02-10 15:58:45 2019-02-10 16:22:47 censo catalog entry 21 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755/MonetDB' 2019-02-10 16:22:47 2019-02-10 16:38:40 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/RR.zip' 2019-02-10 16:38:40 cached in 2019-02-10 16:38:40 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/30da4639719883b3e680399fe5f3f7c5.Rcache' 2019-02-10 16:38:40 copying to 2019-02-10 16:38:40 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpitRJKD/file5557af1cac4' 2019-02-10 16:38:40 2019-02-10 16:43:54 censo catalog entry 22 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755/MonetDB' 2019-02-10 16:43:54 2019-02-10 17:31:44 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/RS.zip' 2019-02-10 17:31:44 cached in 2019-02-10 17:31:44 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/989abcab6ef8f4cc0482c4da694d254e.Rcache' 2019-02-10 17:31:44 copying to 2019-02-10 17:31:44 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpitRJKD/file5557af1cac4' 2019-02-10 17:31:44 2019-02-10 18:26:36 censo catalog entry 23 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755/MonetDB' 2019-02-10 18:26:36 2019-02-10 18:41:07 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/SC.zip' 2019-02-10 18:41:07 cached in 2019-02-10 18:41:07 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/5aa8eea1b7368218b7503d61f196b586.Rcache' 2019-02-10 18:41:07 copying to 2019-02-10 18:41:07 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpitRJKD/file5557af1cac4' 2019-02-10 18:41:07 2019-02-10 18:46:09 censo catalog entry 24 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755/MonetDB' 2019-02-10 18:46:09 2019-02-10 18:49:52 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/SE.zip' 2019-02-10 18:49:52 cached in 2019-02-10 18:49:52 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/af4222637a1c8e705f816d7a78284a2f.Rcache' 2019-02-10 18:49:52 copying to 2019-02-10 18:49:52 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpitRJKD/file5557af1cac4' 2019-02-10 18:49:52 2019-02-10 19:08:02 censo catalog entry 25 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755/MonetDB' 2019-02-10 19:08:02 2019-02-10 19:18:05 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/SP1.zip' 2019-02-10 19:18:05 cached in 2019-02-10 19:18:05 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/5493bb945da3b02e07808de8b2c38054.Rcache' 2019-02-10 19:18:05 copying to 2019-02-10 19:18:05 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpitRJKD/file5557af1cac4' 2019-02-10 19:18:05 2019-02-10 19:34:38 censo catalog entry 26 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755/MonetDB' 2019-02-10 19:34:38 2019-02-10 19:37:41 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/SP2_RM.zip' 2019-02-10 19:37:41 cached in 2019-02-10 19:37:41 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/688c1a930ab09e425507f8e308e0d3cc.Rcache' 2019-02-10 19:37:41 copying to 2019-02-10 19:37:41 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpitRJKD/file5557af1cac4' 2019-02-10 19:37:41 2019-02-10 19:49:13 censo catalog entry 27 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755/MonetDB' 2019-02-10 19:49:13 2019-02-10 19:56:18 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/TO.zip' 2019-02-10 19:56:18 cached in 2019-02-10 19:56:18 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/319c75b43a1d30166e3a0185c3a7d1ad.Rcache' 2019-02-10 19:56:18 copying to 2019-02-10 19:56:18 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpitRJKD/file5557af1cac4' 2019-02-10 19:56:18 2019-02-10 20:34:34 censo catalog entry 28 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755/MonetDB' 2019-02-10 20:34:34 2019-02-10 21:20:37 censo survey design entry 1 of 2 stored at '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755/dom 2010 design.rds' 2019-02-10 21:20:37 2019-02-11 00:12:46 censo survey design entry 2 of 2 stored at '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755/pes 2010 design.rds' 2019-02-11 00:12:47 2019-02-11 00:12:47 censo local download completed 2019-02-11 00:12:47 2019-02-11 00:12:49 Warning message: 2019-02-11 00:12:49 In .Internal(gc(verbose, reset, full)) : 2019-02-11 00:12:49 Connection is garbage-collected, use dbDisconnect() to avoid this. 2019-02-11 00:12:49 > setup return code=0 2019-02-11 00:13:50 2019-02-11 00:13:50 R version 3.5.1 (2018-07-02) -- "Feather Spray" 2019-02-11 00:13:50 Copyright (C) 2018 The R Foundation for Statistical Computing 2019-02-11 00:13:50 Platform: x86_64-pc-linux-gnu (64-bit) 2019-02-11 00:13:50 2019-02-11 00:13:50 R is free software and comes with ABSOLUTELY NO WARRANTY. 2019-02-11 00:13:50 You are welcome to redistribute it under certain conditions. 2019-02-11 00:13:50 Type 'license()' or 'licence()' for distribution details. 2019-02-11 00:13:50 2019-02-11 00:13:50 Natural language support but running in an English locale 2019-02-11 00:13:50 2019-02-11 00:13:50 R is a collaborative project with many contributors. 2019-02-11 00:13:50 Type 'contributors()' for more information and 2019-02-11 00:13:50 'citation()' on how to cite R or R packages in publications. 2019-02-11 00:13:50 2019-02-11 00:13:50 Type 'demo()' for some demos, 'help()' for on-line help, or 2019-02-11 00:13:50 'help.start()' for an HTML browser interface to help. 2019-02-11 00:13:50 Type 'q()' to quit R. 2019-02-11 00:13:50 2019-02-11 00:13:54 > setwd( Sys.getenv( "RWD" ) ) 2019-02-11 00:13:54 > 2019-02-11 00:13:54 > machine_specific_replacements <- 2019-02-11 00:13:54 + list( 2019-02-11 00:13:54 + 2019-02-11 00:13:54 + # replace the folder path on macnix 2019-02-11 00:13:54 + c( 'path.expand( \"~\" ) , \"CENSO\"' , paste0( '"' , getwd() , '"' ) ) , 2019-02-11 00:13:54 + 2019-02-11 00:13:54 + # change other things in the script to be run 2019-02-11 00:13:54 + c( "hello" , "howdy" ) 2019-02-11 00:13:54 + 2019-02-11 00:13:54 + ) 2019-02-11 00:13:54 > 2019-02-11 00:13:54 > source( lodown::syntaxtractor( "censo" , replacements = machine_specific_replacements , setup_test = "test" ) , echo = TRUE ) 2019-02-11 00:13:56 2019-02-11 00:13:56 > library(lodown) 2019-02-11 00:13:56 2019-02-11 00:13:56 > censo_cat <- get_catalog("censo", output_dir = file.path("/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755")) 2019-02-11 00:13:56 building catalog for censo 2019-02-11 00:13:56 2019-02-11 00:14:09 2019-02-11 00:14:09 > censo_cat <- subset(censo_cat, year == 2010) 2019-02-11 00:14:09 2019-02-11 00:14:09 > stopifnot(nrow(censo_cat) > 0) 2019-02-11 00:14:09 2019-02-11 00:14:09 > library(DBI) 2019-02-11 00:14:11 2019-02-11 00:14:11 > library(MonetDBLite) 2019-02-11 00:14:33 2019-02-11 00:14:33 > library(survey) 2019-02-11 00:14:33 Loading required package: grid 2019-02-11 00:14:35 Loading required package: Matrix 2019-02-11 00:14:39 Loading required package: survival 2019-02-11 00:14:44 2019-02-11 00:14:44 Attaching package: ‘survey’ 2019-02-11 00:14:44 2019-02-11 00:14:44 The following object is masked from ‘package:graphics’: 2019-02-11 00:14:44 2019-02-11 00:14:44 dotchart 2019-02-11 00:14:44 2019-02-11 00:14:44 2019-02-11 00:14:44 > options(survey.lonely.psu = "adjust") 2019-02-11 00:14:44 2019-02-11 00:14:44 > censo_design <- readRDS(file.path("/export/scratch1/home/hannes/eanthony/r-wd/censo-1549773755", 2019-02-11 00:14:44 + "pes 2010 design.rds")) 2019-02-11 00:15:08 2019-02-11 00:15:08 > censo_design <- open(censo_design, driver = MonetDBLite()) 2019-02-11 00:24:31 2019-02-11 00:24:31 > censo_design <- update(censo_design, nmorpob1 = ifelse(v6531 >= 2019-02-11 00:24:31 + 0, as.numeric(v6531 < 70), NA), nmorpob2 = ifelse(v6531 >= 2019-02-11 00:24:31 + 0, as.numer .... [TRUNCATED] 2019-02-11 00:24:31 2019-02-11 00:24:31 > sum(weights(censo_design, "sampling") != 0) 2019-02-11 00:24:31 [1] 20635472 2019-02-11 00:24:31 2019-02-11 00:24:31 > svyby(~one, ~state_name, censo_design, unwtd.count) 2019-02-11 00:24:31 QQ: 'SELECT 1' 2019-02-11 00:24:31 II: Finished in 0s 2019-02-11 00:24:31 QQ: 'select one from c10' 2019-02-11 00:24:31 II: Finished in 0s 2019-02-11 00:24:31 QQ: 'SELECT 1' 2019-02-11 00:24:31 II: Finished in 0s 2019-02-11 00:24:31 QQ: 'select v0001 from c10' 2019-02-11 00:24:32 II: Finished in 0.65s 2019-02-11 00:30:41 state_name counts se 2019-02-11 00:30:41 Rondonia Rondonia 195607 0 2019-02-11 00:30:41 Acre Acre 93675 0 2019-02-11 00:30:41 Amazonas Amazonas 295034 0 2019-02-11 00:30:41 Roraima Roraima 63765 0 2019-02-11 00:30:41 Para Para 729094 0 2019-02-11 00:30:41 Amapa Amapa 78344 0 2019-02-11 00:30:41 Tocantins Tocantins 267745 0 2019-02-11 00:30:41 Maranhao Maranhao 793241 0 2019-02-11 00:30:41 Piaui Piaui 496477 0 2019-02-11 00:30:41 Ceara Ceara 846164 0 2019-02-11 00:30:41 Rio Grande do Norte Rio Grande do Norte 424586 0 2019-02-11 00:30:41 Paraiba Paraiba 571631 0 2019-02-11 00:30:41 Pernambuco Pernambuco 892250 0 2019-02-11 00:30:41 Alagoas Alagoas 349966 0 2019-02-11 00:30:41 Sergipe Sergipe 245354 0 2019-02-11 00:30:41 Bahia Bahia 1550842 0 2019-02-11 00:30:41 Minas Gerais Minas Gerais 2506265 0 2019-02-11 00:30:41 Espirito Santo Espirito Santo 400130 0 2019-02-11 00:30:41 Rio de Janeiro Rio de Janeiro 1143650 0 2019-02-11 00:30:41 Sao Paulo Sao Paulo 3651181 0 2019-02-11 00:30:41 Parana Parana 1293034 0 2019-02-11 00:30:41 Santa Catarina Santa Catarina 872242 0 2019-02-11 00:30:41 Rio Grande do Sul Rio Grande do Sul 1388443 0 2019-02-11 00:30:41 Mato Grosso do Sul Mato Grosso do Sul 276714 0 2019-02-11 00:30:41 Mato Grosso Mato Grosso 386537 0 2019-02-11 00:30:41 Goias Goias 707043 0 2019-02-11 00:30:41 Distrito Federal Distrito Federal 116458 0 2019-02-11 00:30:41 2019-02-11 00:30:41 > svytotal(~one, censo_design) 2019-02-11 00:30:41 QQ: 'SELECT 1' 2019-02-11 00:31:01 II: Finished in 19.15s 2019-02-11 00:31:01 QQ: 'select one from c10' 2019-02-11 00:31:01 II: Finished in 0s 2019-02-11 00:31:38 total SE 2019-02-11 00:31:40 one 190755799 53913 2019-02-11 00:31:40 2019-02-11 00:31:40 > svyby(~one, ~state_name, censo_design, svytotal) 2019-02-11 00:31:40 QQ: 'SELECT 1' 2019-02-11 00:31:40 II: Finished in 0s 2019-02-11 00:31:40 QQ: 'select one from c10' 2019-02-11 00:31:40 II: Finished in 0s 2019-02-11 00:31:40 QQ: 'SELECT 1' 2019-02-11 00:31:40 II: Finished in 0s 2019-02-11 00:31:40 QQ: 'select v0001 from c10' 2019-02-11 00:31:40 II: Finished in 0.25s 2019-02-11 00:35:51 state_name one se 2019-02-11 00:35:51 Rondonia Rondonia 1562409 3997.288 2019-02-11 00:35:51 Acre Acre 733559 2756.677 2019-02-11 00:35:51 Amazonas Amazonas 3483985 8539.797 2019-02-11 00:35:51 Roraima Roraima 450479 3029.841 2019-02-11 00:35:51 Para Para 7581051 10813.294 2019-02-11 00:35:51 Amapa Amapa 669526 3616.130 2019-02-11 00:35:51 Tocantins Tocantins 1383445 3489.950 2019-02-11 00:35:51 Maranhao Maranhao 6574789 10703.528 2019-02-11 00:35:51 Piaui Piaui 3118360 5957.131 2019-02-11 00:35:51 Ceara Ceara 8452381 9878.040 2019-02-11 00:35:51 Rio Grande do Norte Rio Grande do Norte 3168027 5790.231 2019-02-11 00:35:51 Paraiba Paraiba 3766528 5321.553 2019-02-11 00:35:51 Pernambuco Pernambuco 8796448 11113.033 2019-02-11 00:35:51 Alagoas Alagoas 3120494 6089.570 2019-02-11 00:35:51 Sergipe Sergipe 2068017 4669.304 2019-02-11 00:35:51 Bahia Bahia 14016906 12785.889 2019-02-11 00:35:51 Minas Gerais Minas Gerais 19597330 15723.440 2019-02-11 00:35:51 Espirito Santo Espirito Santo 3514952 5965.071 2019-02-11 00:35:51 Rio de Janeiro Rio de Janeiro 15989929 17523.921 2019-02-11 00:35:51 Sao Paulo Sao Paulo 41262199 24920.718 2019-02-11 00:35:51 Parana Parana 10444526 10538.560 2019-02-11 00:35:51 Santa Catarina Santa Catarina 6248436 6497.115 2019-02-11 00:35:51 Rio Grande do Sul Rio Grande do Sul 10693929 10443.057 2019-02-11 00:35:51 Mato Grosso do Sul Mato Grosso do Sul 2449024 5200.997 2019-02-11 00:35:51 Mato Grosso Mato Grosso 3035122 6050.717 2019-02-11 00:35:51 Goias Goias 6003788 9394.544 2019-02-11 00:35:51 Distrito Federal Distrito Federal 2570160 7697.785 2019-02-11 00:35:51 2019-02-11 00:35:51 > svymean(~v6033, censo_design) 2019-02-11 00:35:51 QQ: 'SELECT 1' 2019-02-11 00:35:51 II: Finished in 0s 2019-02-11 00:35:51 QQ: 'select v6033 from c10' 2019-02-11 00:35:51 II: Finished in 0s 2019-02-11 00:36:38 mean SE 2019-02-11 00:36:38 v6033 44.532 0.024 2019-02-11 00:36:38 2019-02-11 00:36:38 > svyby(~v6033, ~state_name, censo_design, svymean) 2019-02-11 00:36:38 QQ: 'SELECT 1' 2019-02-11 00:36:38 II: Finished in 0s 2019-02-11 00:36:38 QQ: 'select v6033 from c10' 2019-02-11 00:36:38 II: Finished in 0s 2019-02-11 00:36:38 QQ: 'SELECT 1' 2019-02-11 00:36:38 II: Finished in 0s 2019-02-11 00:36:38 QQ: 'select v0001 from c10' 2019-02-11 00:36:39 II: Finished in 0.19s 2019-02-11 00:40:14 state_name v6033 se 2019-02-11 00:40:14 Rondonia Rondonia 43.47609 0.27249280 2019-02-11 00:40:14 Acre Acre 44.14539 0.44043973 2019-02-11 00:40:14 Amazonas Amazonas 44.89294 0.24303428 2019-02-11 00:40:14 Roraima Roraima 44.61115 0.53712682 2019-02-11 00:40:14 Para Para 44.06793 0.15094624 2019-02-11 00:40:14 Amapa Amapa 44.36371 0.45909609 2019-02-11 00:40:14 Tocantins Tocantins 44.08827 0.26433095 2019-02-11 00:40:14 Maranhao Maranhao 44.39162 0.13223921 2019-02-11 00:40:14 Piaui Piaui 44.23805 0.18469341 2019-02-11 00:40:14 Ceara Ceara 43.97193 0.11708930 2019-02-11 00:40:14 Rio Grande do Norte Rio Grande do Norte 44.05621 0.20679648 2019-02-11 00:40:14 Paraiba Paraiba 45.40817 0.16461203 2019-02-11 00:40:14 Pernambuco Pernambuco 44.35515 0.13112504 2019-02-11 00:40:14 Alagoas Alagoas 44.39060 0.23015269 2019-02-11 00:40:14 Sergipe Sergipe 43.67018 0.25002416 2019-02-11 00:40:14 Bahia Bahia 44.00062 0.08948862 2019-02-11 00:40:14 Minas Gerais Minas Gerais 44.22639 0.06728968 2019-02-11 00:40:14 Espirito Santo Espirito Santo 44.43069 0.18167442 2019-02-11 00:40:14 Rio de Janeiro Rio de Janeiro 45.11529 0.10052635 2019-02-11 00:40:14 Sao Paulo Sao Paulo 44.86147 0.06331691 2019-02-11 00:40:14 Parana Parana 44.88411 0.10435709 2019-02-11 00:40:14 Santa Catarina Santa Catarina 44.42404 0.11504320 2019-02-11 00:40:14 Rio Grande do Sul Rio Grande do Sul 45.18820 0.09119389 2019-02-11 00:40:14 Mato Grosso do Sul Mato Grosso do Sul 45.08575 0.23087339 2019-02-11 00:40:14 Mato Grosso Mato Grosso 43.70309 0.19892459 2019-02-11 00:40:14 Goias Goias 44.16120 0.16194948 2019-02-11 00:40:14 Distrito Federal Distrito Federal 43.61118 0.31517846 2019-02-11 00:40:14 2019-02-11 00:40:14 > svymean(~sexo, censo_design) 2019-02-11 00:40:14 QQ: 'SELECT 1' 2019-02-11 00:40:14 II: Finished in 0s 2019-02-11 00:40:14 QQ: 'select v0601 from c10' 2019-02-11 00:40:16 II: Finished in 1.6s 2019-02-11 00:40:51 mean SE 2019-02-11 00:40:51 sexomasculino 0.48967 1e-04 2019-02-11 00:40:51 sexofeminino 0.51033 1e-04 2019-02-11 00:40:51 2019-02-11 00:40:51 > svyby(~sexo, ~state_name, censo_design, svymean) 2019-02-11 00:40:51 QQ: 'SELECT 1' 2019-02-11 00:41:02 II: Finished in 10.62s 2019-02-11 00:41:02 QQ: 'select v0601 from c10' 2019-02-11 00:41:02 II: Finished in 0.12s 2019-02-11 00:41:02 QQ: 'SELECT 1' 2019-02-11 00:41:02 II: Finished in 0s 2019-02-11 00:41:02 QQ: 'select v0001 from c10' 2019-02-11 00:41:03 II: Finished in 0.14s 2019-02-11 00:44:48 state_name sexomasculino sexofeminino se1 2019-02-11 00:44:48 Rondonia Rondonia 0.5089301 0.4910699 0.0008419612 2019-02-11 00:44:48 Acre Acre 0.5021055 0.4978945 0.0014231562 2019-02-11 00:44:48 Amazonas Amazonas 0.5032108 0.4967892 0.0007855080 2019-02-11 00:44:48 Roraima Roraima 0.5080348 0.4919652 0.0013171408 2019-02-11 00:44:48 Para Para 0.5041302 0.4958698 0.0005688695 2019-02-11 00:44:48 Amapa Amapa 0.5005556 0.4994444 0.0014255383 2019-02-11 00:44:48 Tocantins Tocantins 0.5077354 0.4922646 0.0009019894 2019-02-11 00:44:48 Maranhao Maranhao 0.4960638 0.5039362 0.0005764131 2019-02-11 00:44:48 Piaui Piaui 0.4901365 0.5098635 0.0006691581 2019-02-11 00:44:48 Ceara Ceara 0.4874470 0.5125530 0.0005276184 2019-02-11 00:44:48 Rio Grande do Norte Rio Grande do Norte 0.4889122 0.5110878 0.0006117453 2019-02-11 00:44:48 Paraiba Paraiba 0.4843662 0.5156338 0.0006226393 2019-02-11 00:44:48 Pernambuco Pernambuco 0.4809533 0.5190467 0.0004462301 2019-02-11 00:44:48 Alagoas Alagoas 0.4844640 0.5155360 0.0008136156 2019-02-11 00:44:48 Sergipe Sergipe 0.4859926 0.5140074 0.0009800888 2019-02-11 00:44:48 Bahia Bahia 0.4907121 0.5092879 0.0003506238 2019-02-11 00:44:48 Minas Gerais Minas Gerais 0.4919995 0.5080005 0.0002942877 2019-02-11 00:44:48 Espirito Santo Espirito Santo 0.4925296 0.5074704 0.0006447842 2019-02-11 00:44:48 Rio de Janeiro Rio de Janeiro 0.4769051 0.5230949 0.0004205925 2019-02-11 00:44:48 Sao Paulo Sao Paulo 0.4865924 0.5134076 0.0002302002 2019-02-11 00:44:48 Parana Parana 0.4912615 0.5087385 0.0004277059 2019-02-11 00:44:48 Santa Catarina Santa Catarina 0.4961818 0.5038182 0.0004193186 2019-02-11 00:44:48 Rio Grande do Sul Rio Grande do Sul 0.4867301 0.5132699 0.0003390903 2019-02-11 00:44:48 Mato Grosso do Sul Mato Grosso do Sul 0.4981282 0.5018718 0.0009161308 2019-02-11 00:44:48 Mato Grosso Mato Grosso 0.5105350 0.4894650 0.0006402044 2019-02-11 00:44:48 Goias Goias 0.4966243 0.5033757 0.0005607331 2019-02-11 00:44:48 Distrito Federal Distrito Federal 0.4781337 0.5218663 0.0011130223 2019-02-11 00:44:48 se2 2019-02-11 00:44:48 Rondonia 0.0008419612 2019-02-11 00:44:48 Acre 0.0014231562 2019-02-11 00:44:48 Amazonas 0.0007855080 2019-02-11 00:44:48 Roraima 0.0013171408 2019-02-11 00:44:48 Para 0.0005688695 2019-02-11 00:44:48 Amapa 0.0014255383 2019-02-11 00:44:48 Tocantins 0.0009019894 2019-02-11 00:44:48 Maranhao 0.0005764131 2019-02-11 00:44:48 Piaui 0.0006691581 2019-02-11 00:44:48 Ceara 0.0005276184 2019-02-11 00:44:48 Rio Grande do Norte 0.0006117453 2019-02-11 00:44:48 Paraiba 0.0006226393 2019-02-11 00:44:48 Pernambuco 0.0004462301 2019-02-11 00:44:48 Alagoas 0.0008136156 2019-02-11 00:44:48 Sergipe 0.0009800888 2019-02-11 00:44:48 Bahia 0.0003506238 2019-02-11 00:44:48 Minas Gerais 0.0002942877 2019-02-11 00:44:48 Espirito Santo 0.0006447842 2019-02-11 00:44:48 Rio de Janeiro 0.0004205925 2019-02-11 00:44:48 Sao Paulo 0.0002302002 2019-02-11 00:44:48 Parana 0.0004277059 2019-02-11 00:44:48 Santa Catarina 0.0004193186 2019-02-11 00:44:48 Rio Grande do Sul 0.0003390903 2019-02-11 00:44:48 Mato Grosso do Sul 0.0009161308 2019-02-11 00:44:48 Mato Grosso 0.0006402044 2019-02-11 00:44:48 Goias 0.0005607331 2019-02-11 00:44:48 Distrito Federal 0.0011130223 2019-02-11 00:44:48 2019-02-11 00:44:48 > svytotal(~v6033, censo_design) 2019-02-11 00:44:48 QQ: 'SELECT 1' 2019-02-11 00:44:48 II: Finished in 0s 2019-02-11 00:44:48 QQ: 'select v6033 from c10' 2019-02-11 00:44:48 II: Finished in 0s 2019-02-11 00:45:06 total SE 2019-02-11 00:45:06 v6033 8494688084 5402064 2019-02-11 00:45:06 2019-02-11 00:45:06 > svyby(~v6033, ~state_name, censo_design, svytotal) 2019-02-11 00:45:06 QQ: 'SELECT 1' 2019-02-11 00:45:06 II: Finished in 0s 2019-02-11 00:45:06 QQ: 'select v6033 from c10' 2019-02-11 00:45:06 II: Finished in 0s 2019-02-11 00:45:06 QQ: 'SELECT 1' 2019-02-11 00:45:06 II: Finished in 0s 2019-02-11 00:45:06 QQ: 'select v0001 from c10' 2019-02-11 00:45:06 II: Finished in 0.14s 2019-02-11 00:48:37 state_name v6033 se 2019-02-11 00:48:37 Rondonia Rondonia 67927439 420260.3 2019-02-11 00:48:37 Acre Acre 32383247 327460.9 2019-02-11 00:48:37 Amazonas Amazonas 156406314 983606.0 2019-02-11 00:48:37 Roraima Roraima 20096387 275481.3 2019-02-11 00:48:37 Para Para 334081201 1296927.0 2019-02-11 00:48:37 Amapa Amapa 29702659 338915.0 2019-02-11 00:48:37 Tocantins Tocantins 60993702 388685.1 2019-02-11 00:48:37 Maranhao Maranhao 291865565 1014535.2 2019-02-11 00:48:37 Piaui Piaui 137950175 603074.7 2019-02-11 00:48:37 Ceara Ceara 371667509 1077974.3 2019-02-11 00:48:37 Rio Grande do Norte Rio Grande do Norte 139571251 723472.3 2019-02-11 00:48:37 Paraiba Paraiba 171031139 642766.2 2019-02-11 00:48:37 Pernambuco Pernambuco 390167775 1286159.3 2019-02-11 00:48:37 Alagoas Alagoas 138520597 788911.4 2019-02-11 00:48:37 Sergipe Sergipe 90310670 566605.1 2019-02-11 00:48:37 Bahia Bahia 616752560 1332982.4 2019-02-11 00:48:37 Minas Gerais Minas Gerais 866719202 1549584.5 2019-02-11 00:48:37 Espirito Santo Espirito Santo 156171746 683158.3 2019-02-11 00:48:37 Rio de Janeiro Rio de Janeiro 721390292 1834155.0 2019-02-11 00:48:37 Sao Paulo Sao Paulo 1851082734 2966388.9 2019-02-11 00:48:37 Parana Parana 468793290 1203145.8 2019-02-11 00:48:37 Santa Catarina Santa Catarina 277580763 730385.9 2019-02-11 00:48:37 Rio Grande do Sul Rio Grande do Sul 483239360 1034720.5 2019-02-11 00:48:37 Mato Grosso do Sul Mato Grosso do Sul 110416076 591684.2 2019-02-11 00:48:37 Mato Grosso Mato Grosso 132644212 666820.0 2019-02-11 00:48:37 Goias Goias 265134506 1113622.8 2019-02-11 00:48:37 Distrito Federal Distrito Federal 112087713 936713.6 2019-02-11 00:48:37 2019-02-11 00:48:37 > svytotal(~sexo, censo_design) 2019-02-11 00:48:37 QQ: 'SELECT 1' 2019-02-11 00:48:37 II: Finished in 0s 2019-02-11 00:48:37 QQ: 'select v0601 from c10' 2019-02-11 00:48:37 II: Finished in 0.11s 2019-02-11 00:49:04 total SE 2019-02-11 00:49:04 sexomasculino 93406990 29170 2019-02-11 00:49:04 sexofeminino 97348809 39174 2019-02-11 00:49:04 2019-02-11 00:49:04 > svyby(~sexo, ~state_name, censo_design, svytotal) 2019-02-11 00:49:04 QQ: 'SELECT 1' 2019-02-11 00:49:04 II: Finished in 0s 2019-02-11 00:49:04 QQ: 'select v0601 from c10' 2019-02-11 00:49:05 II: Finished in 0.11s 2019-02-11 00:49:06 QQ: 'SELECT 1' 2019-02-11 00:49:06 II: Finished in 0s 2019-02-11 00:49:06 QQ: 'select v0001 from c10' 2019-02-11 00:49:06 II: Finished in 0.14s 2019-02-11 00:52:46 state_name sexomasculino sexofeminino se1 2019-02-11 00:52:46 Rondonia Rondonia 795157 767252 2427.900 2019-02-11 00:52:46 Acre Acre 368324 365235 1755.362 2019-02-11 00:52:46 Amazonas Amazonas 1753179 1730806 4591.156 2019-02-11 00:52:46 Roraima Roraima 228859 221620 1548.703 2019-02-11 00:52:46 Para Para 3821837 3759214 6998.866 2019-02-11 00:52:46 Amapa Amapa 335135 334391 2064.021 2019-02-11 00:52:46 Tocantins Tocantins 702424 681021 2252.328 2019-02-11 00:52:46 Maranhao Maranhao 3261515 3313274 7210.928 2019-02-11 00:52:46 Piaui Piaui 1528422 1589938 3583.372 2019-02-11 00:52:46 Ceara Ceara 4120088 4332293 6583.979 2019-02-11 00:52:46 Rio Grande do Norte Rio Grande do Norte 1548887 1619140 3540.745 2019-02-11 00:52:46 Paraiba Paraiba 1824379 1942149 3496.975 2019-02-11 00:52:46 Pernambuco Pernambuco 4230681 4565767 6286.239 2019-02-11 00:52:46 Alagoas Alagoas 1511767 1608727 3692.213 2019-02-11 00:52:46 Sergipe Sergipe 1005041 1062976 3100.173 2019-02-11 00:52:46 Bahia Bahia 6878266 7138640 7595.906 2019-02-11 00:52:46 Minas Gerais Minas Gerais 9641877 9955453 9213.197 2019-02-11 00:52:46 Espirito Santo Espirito Santo 1731218 1783734 3941.444 2019-02-11 00:52:46 Rio de Janeiro Rio de Janeiro 7625679 8364250 10193.345 2019-02-11 00:52:46 Sao Paulo Sao Paulo 20077873 21184326 14910.130 2019-02-11 00:52:46 Parana Parana 5130994 5313532 7602.918 2019-02-11 00:52:46 Santa Catarina Santa Catarina 3100360 3148076 4143.981 2019-02-11 00:52:46 Rio Grande do Sul Rio Grande do Sul 5205057 5488872 6333.590 2019-02-11 00:52:46 Mato Grosso do Sul Mato Grosso do Sul 1219928 1229096 3489.724 2019-02-11 00:52:46 Mato Grosso Mato Grosso 1549536 1485586 3573.390 2019-02-11 00:52:46 Goias Goias 2981627 3022161 5318.821 2019-02-11 00:52:46 Distrito Federal Distrito Federal 1228880 1341280 4365.736 2019-02-11 00:52:46 se2 2019-02-11 00:52:46 Rondonia 2358.506 2019-02-11 00:52:46 Acre 1702.846 2019-02-11 00:52:46 Amazonas 5506.208 2019-02-11 00:52:46 Roraima 1699.175 2019-02-11 00:52:46 Para 6832.064 2019-02-11 00:52:46 Amapa 2025.354 2019-02-11 00:52:46 Tocantins 2036.319 2019-02-11 00:52:46 Maranhao 5821.082 2019-02-11 00:52:46 Piaui 3691.645 2019-02-11 00:52:46 Ceara 6724.935 2019-02-11 00:52:46 Rio Grande do Norte 3423.430 2019-02-11 00:52:46 Paraiba 3596.359 2019-02-11 00:52:46 Pernambuco 7315.225 2019-02-11 00:52:46 Alagoas 4234.757 2019-02-11 00:52:46 Sergipe 3080.654 2019-02-11 00:52:46 Bahia 8519.277 2019-02-11 00:52:46 Minas Gerais 10273.157 2019-02-11 00:52:46 Espirito Santo 3533.788 2019-02-11 00:52:46 Rio de Janeiro 11896.781 2019-02-11 00:52:46 Sao Paulo 16423.237 2019-02-11 00:52:46 Parana 6105.800 2019-02-11 00:52:46 Santa Catarina 4203.542 2019-02-11 00:52:46 Rio Grande do Sul 6378.402 2019-02-11 00:52:46 Mato Grosso do Sul 3377.252 2019-02-11 00:52:46 Mato Grosso 3615.119 2019-02-11 00:52:46 Goias 6210.845 2019-02-11 00:52:46 Distrito Federal 5219.927 2019-02-11 00:52:46 2019-02-11 00:52:46 > svyquantile(~v6033, censo_design, 0.5) 2019-02-11 00:52:46 QQ: 'SELECT 1' 2019-02-11 00:52:46 II: Finished in 0s 2019-02-11 00:52:46 QQ: 'select v6033 from c10' 2019-02-11 00:52:46 II: Finished in 0s 2019-02-11 00:53:20 QQ: 'SELECT 1' 2019-02-11 00:53:20 II: Finished in 0s 2019-02-11 00:54:06 Statistic: 2019-02-11 00:54:06 v6033 2019-02-11 00:54:06 q0.5 30 2019-02-11 00:54:06 SE: 2019-02-11 00:54:06 v6033 2019-02-11 00:54:06 q0.5 0.25 2019-02-11 00:54:06 2019-02-11 00:54:06 > svyby(~v6033, ~state_name, censo_design, svyquantile, 2019-02-11 00:54:06 + 0.5, ci = TRUE, keep.var = TRUE) 2019-02-11 00:54:06 QQ: 'SELECT 1' 2019-02-11 00:57:03 II: Finished in 2.96s 2019-02-11 00:57:05 QQ: 'select v6033 from c10' 2019-02-11 00:57:05 II: Finished in 0s 2019-02-11 00:57:05 QQ: 'SELECT 1' 2019-02-11 00:57:05 II: Finished in 0s 2019-02-11 00:57:05 QQ: 'select v0001 from c10' 2019-02-11 00:57:05 II: Finished in 0.25s 2019-02-11 01:01:07 state_name V1 se 2019-02-11 01:01:10 Rondonia Rondonia 27 0.25 2019-02-11 01:01:10 Acre Acre 24 0.25 2019-02-11 01:01:10 Amazonas Amazonas 24 0.25 2019-02-11 01:01:10 Roraima Roraima 24 0.25 2019-02-11 01:01:10 Para Para 25 0.25 2019-02-11 01:01:10 Amapa Amapa 23 0.25 2019-02-11 01:01:10 Tocantins Tocantins 26 0.25 2019-02-11 01:01:10 Maranhao Maranhao 25 0.25 2019-02-11 01:01:10 Piaui Piaui 28 0.25 2019-02-11 01:01:10 Ceara Ceara 28 0.25 2019-02-11 01:01:10 Rio Grande do Norte Rio Grande do Norte 29 0.25 2019-02-11 01:01:10 Paraiba Paraiba 29 0.25 2019-02-11 01:01:10 Pernambuco Pernambuco 29 0.25 2019-02-11 01:01:10 Alagoas Alagoas 26 0.25 2019-02-11 01:01:10 Sergipe Sergipe 27 0.25 2019-02-11 01:01:10 Bahia Bahia 28 0.25 2019-02-11 01:01:10 Minas Gerais Minas Gerais 31 0.25 2019-02-11 01:01:10 Espirito Santo Espirito Santo 30 0.25 2019-02-11 01:01:10 Rio de Janeiro Rio de Janeiro 33 0.25 2019-02-11 01:01:10 Sao Paulo Sao Paulo 32 0.25 2019-02-11 01:01:10 Parana Parana 31 0.25 2019-02-11 01:01:10 Santa Catarina Santa Catarina 31 0.25 2019-02-11 01:01:10 Rio Grande do Sul Rio Grande do Sul 33 0.25 2019-02-11 01:01:10 Mato Grosso do Sul Mato Grosso do Sul 29 0.25 2019-02-11 01:01:10 Mato Grosso Mato Grosso 28 0.25 2019-02-11 01:01:10 Goias Goias 30 0.25 2019-02-11 01:01:10 Distrito Federal Distrito Federal 29 0.25 2019-02-11 01:01:10 2019-02-11 01:01:10 > svyratio(numerator = ~nmorpob1, denominator = ~nmorpob1 + 2019-02-11 01:01:10 + one, censo_design, na.rm = TRUE) 2019-02-11 01:01:10 QQ: 'SELECT 1' 2019-02-11 01:01:10 II: Finished in 0s 2019-02-11 01:01:10 QQ: 'select v6531 from c10' 2019-02-11 01:01:36 II: Finished in 28.85s 2019-02-11 01:01:37 QQ: 'SELECT 1' 2019-02-11 01:01:37 II: Finished in 0s 2019-02-11 01:01:37 QQ: 'select one, v6531 from c10' 2019-02-11 01:01:37 II: Finished in 0.03s 2019-02-11 01:06:06 QQ: 'SELECT 1' 2019-02-11 01:10:22 II: Finished in 4.26s 2019-02-11 01:11:13 Ratio estimator: svyratio.svyrep.design(numerator = ~nmorpob1, denominator = ~nmorpob1 + 2019-02-11 01:11:13 one, censo_design, na.rm = TRUE) 2019-02-11 01:11:13 Ratios= 2019-02-11 01:11:13 nmorpob1 one 2019-02-11 01:11:13 nmorpob1 1 0.09317731 2019-02-11 01:11:13 SEs= 2019-02-11 01:11:13 [,1] [,2] 2019-02-11 01:11:13 [1,] 0 0.000166458 2019-02-11 01:11:13 2019-02-11 01:11:13 > sub_censo_design <- subset(censo_design, v0640 == 2019-02-11 01:11:13 + 1) 2019-02-11 01:11:13 QQ: 'SELECT 1' 2019-02-11 01:12:15 II: Finished in 1.04s 2019-02-11 01:12:17 QQ: 'select v0640 from c10' 2019-02-11 01:12:17 II: Finished in 1.27s 2019-02-11 01:13:16 2019-02-11 01:13:16 > svymean(~v6033, sub_censo_design) 2019-02-11 01:13:16 QQ: 'SELECT 1' 2019-02-11 01:13:22 II: Finished in 6.39s 2019-02-11 01:13:22 QQ: 'select v6033 from c10' 2019-02-11 01:13:22 II: Finished in 0s 2019-02-11 01:13:35 mean SE 2019-02-11 01:13:35 v6033 45.922 0.0091 2019-02-11 01:13:35 2019-02-11 01:13:35 > this_result <- svymean(~v6033, censo_design) 2019-02-11 01:13:35 QQ: 'SELECT 1' 2019-02-11 01:13:35 II: Finished in 0s 2019-02-11 01:13:35 QQ: 'select v6033 from c10' 2019-02-11 01:13:35 II: Finished in 0s 2019-02-11 01:14:07 2019-02-11 01:14:07 > coef(this_result) 2019-02-11 01:14:07 v6033 2019-02-11 01:14:07 44.53174 2019-02-11 01:14:07 2019-02-11 01:14:07 > SE(this_result) 2019-02-11 01:14:07 [1] 0.02396853 2019-02-11 01:14:07 2019-02-11 01:14:07 > confint(this_result) 2019-02-11 01:14:07 2.5 % 97.5 % 2019-02-11 01:14:07 v6033 44.48476 44.57872 2019-02-11 01:14:07 2019-02-11 01:14:07 > cv(this_result) 2019-02-11 01:14:07 v6033 2019-02-11 01:14:07 0.0005382347 2019-02-11 01:14:07 2019-02-11 01:14:07 > grouped_result <- svyby(~v6033, ~state_name, censo_design, 2019-02-11 01:14:07 + svymean) 2019-02-11 01:14:07 QQ: 'SELECT 1' 2019-02-11 01:14:07 II: Finished in 0s 2019-02-11 01:14:07 QQ: 'select v6033 from c10' 2019-02-11 01:14:07 II: Finished in 0s 2019-02-11 01:14:07 QQ: 'SELECT 1' 2019-02-11 01:14:07 II: Finished in 0s 2019-02-11 01:14:07 QQ: 'select v0001 from c10' 2019-02-11 01:14:07 II: Finished in 0.19s 2019-02-11 01:17:55 2019-02-11 01:17:55 > coef(grouped_result) 2019-02-11 01:17:55 Rondonia Acre Amazonas Roraima 2019-02-11 01:17:55 43.47609 44.14539 44.89294 44.61115 2019-02-11 01:17:55 Para Amapa Tocantins Maranhao 2019-02-11 01:17:55 44.06793 44.36371 44.08827 44.39162 2019-02-11 01:17:55 Piaui Ceara Rio Grande do Norte Paraiba 2019-02-11 01:17:55 44.23805 43.97193 44.05621 45.40817 2019-02-11 01:17:55 Pernambuco Alagoas Sergipe Bahia 2019-02-11 01:17:55 44.35515 44.39060 43.67018 44.00062 2019-02-11 01:17:55 Minas Gerais Espirito Santo Rio de Janeiro Sao Paulo 2019-02-11 01:17:55 44.22639 44.43069 45.11529 44.86147 2019-02-11 01:17:55 Parana Santa Catarina Rio Grande do Sul Mato Grosso do Sul 2019-02-11 01:17:55 44.88411 44.42404 45.18820 45.08575 2019-02-11 01:17:55 Mato Grosso Goias Distrito Federal 2019-02-11 01:17:55 43.70309 44.16120 43.61118 2019-02-11 01:17:55 2019-02-11 01:17:55 > SE(grouped_result) 2019-02-11 01:17:55 [1] 0.27249280 0.44043973 0.24303428 0.53712682 0.15094624 0.45909609 2019-02-11 01:17:55 [7] 0.26433095 0.13223921 0.18469341 0.11708930 0.20679648 0.16461203 2019-02-11 01:17:55 [13] 0.13112504 0.23015269 0.25002416 0.08948862 0.06728968 0.18167442 2019-02-11 01:17:55 [19] 0.10052635 0.06331691 0.10435709 0.11504320 0.09119389 0.23087339 2019-02-11 01:17:55 [25] 0.19892459 0.16194948 0.31517846 2019-02-11 01:17:55 2019-02-11 01:17:55 > confint(grouped_result) 2019-02-11 01:17:55 2.5 % 97.5 % 2019-02-11 01:17:55 Rondonia 42.94202 44.01017 2019-02-11 01:17:55 Acre 43.28214 45.00863 2019-02-11 01:17:55 Amazonas 44.41660 45.36927 2019-02-11 01:17:55 Roraima 43.55840 45.66390 2019-02-11 01:17:55 Para 43.77208 44.36378 2019-02-11 01:17:55 Amapa 43.46390 45.26352 2019-02-11 01:17:55 Tocantins 43.57019 44.60635 2019-02-11 01:17:55 Maranhao 44.13244 44.65081 2019-02-11 01:17:55 Piaui 43.87606 44.60005 2019-02-11 01:17:55 Ceara 43.74244 44.20142 2019-02-11 01:17:55 Rio Grande do Norte 43.65089 44.46152 2019-02-11 01:17:55 Paraiba 45.08554 45.73080 2019-02-11 01:17:55 Pernambuco 44.09815 44.61215 2019-02-11 01:17:55 Alagoas 43.93951 44.84169 2019-02-11 01:17:55 Sergipe 43.18014 44.16022 2019-02-11 01:17:55 Bahia 43.82523 44.17601 2019-02-11 01:17:55 Minas Gerais 44.09451 44.35828 2019-02-11 01:17:55 Espirito Santo 44.07462 44.78677 2019-02-11 01:17:55 Rio de Janeiro 44.91826 45.31232 2019-02-11 01:17:55 Sao Paulo 44.73737 44.98556 2019-02-11 01:17:55 Parana 44.67958 45.08865 2019-02-11 01:17:55 Santa Catarina 44.19856 44.64952 2019-02-11 01:17:55 Rio Grande do Sul 45.00946 45.36693 2019-02-11 01:17:55 Mato Grosso do Sul 44.63324 45.53825 2019-02-11 01:17:55 Mato Grosso 43.31321 44.09298 2019-02-11 01:17:55 Goias 43.84379 44.47862 2019-02-11 01:17:55 Distrito Federal 42.99344 44.22892 2019-02-11 01:17:55 2019-02-11 01:17:55 > cv(grouped_result) 2019-02-11 01:17:55 Rondonia Acre Amazonas Roraima 2019-02-11 01:17:55 0.006267647 0.009977027 0.005413642 0.012040192 2019-02-11 01:17:55 Para Amapa Tocantins Maranhao 2019-02-11 01:17:55 0.003425308 0.010348460 0.005995493 0.002978923 2019-02-11 01:17:55 Piaui Ceara Rio Grande do Norte Paraiba 2019-02-11 01:17:55 0.004174990 0.002662819 0.004693924 0.003625163 2019-02-11 01:17:55 Pernambuco Alagoas Sergipe Bahia 2019-02-11 01:17:55 0.002956253 0.005184717 0.005725284 0.002033804 2019-02-11 01:17:55 Minas Gerais Espirito Santo Rio de Janeiro Sao Paulo 2019-02-11 01:17:55 0.001521483 0.004088940 0.002228210 0.001411388 2019-02-11 01:17:55 Parana Santa Catarina Rio Grande do Sul Mato Grosso do Sul 2019-02-11 01:17:55 0.002325034 0.002589661 0.002018091 0.005120762 2019-02-11 01:17:55 Mato Grosso Goias Distrito Federal 2019-02-11 01:17:55 0.004551728 0.003667234 0.007227010 2019-02-11 01:17:55 2019-02-11 01:17:55 > degf(censo_design) 2019-02-11 01:17:55 [1] 79 2019-02-11 01:17:55 2019-02-11 01:17:55 > svyvar(~v6033, censo_design) 2019-02-11 01:17:55 QQ: 'SELECT 1' 2019-02-11 01:17:55 II: Finished in 0s 2019-02-11 01:17:55 QQ: 'select v6033 from c10' 2019-02-11 01:17:55 II: Finished in 0s 2019-02-11 01:19:28 variance SE 2019-02-11 01:19:28 v6033 11161 20.79 2019-02-11 01:19:28 2019-02-11 01:19:28 > svymean(~v6033, censo_design, deff = TRUE) 2019-02-11 01:19:28 QQ: 'SELECT 1' 2019-02-11 01:19:28 II: Finished in 0s 2019-02-11 01:19:28 QQ: 'select v6033 from c10' 2019-02-11 01:19:28 II: Finished in 0s 2019-02-11 01:19:53 QQ: 'SELECT 1' 2019-02-11 01:19:53 II: Finished in 0s 2019-02-11 01:19:54 mean SE DEff 2019-02-11 01:19:54 v6033 44.531742 0.023969 1.191 2019-02-11 01:19:54 2019-02-11 01:19:54 > svymean(~v6033, censo_design, deff = "replace") 2019-02-11 01:19:54 QQ: 'SELECT 1' 2019-02-11 01:19:54 II: Finished in 0s 2019-02-11 01:19:54 QQ: 'select v6033 from c10' 2019-02-11 01:19:54 II: Finished in 0s 2019-02-11 01:20:21 QQ: 'SELECT 1' 2019-02-11 01:21:01 II: Finished in 40s 2019-02-11 01:21:01 mean SE DEff 2019-02-11 01:21:01 v6033 44.531742 0.023969 1.0622 2019-02-11 01:21:01 2019-02-11 01:21:01 > svyciprop(~nmorpob6, censo_design, method = "likelihood", 2019-02-11 01:21:01 + na.rm = TRUE) 2019-02-11 01:21:19 QQ: 'SELECT 1' 2019-02-11 01:21:19 II: Finished in 0s 2019-02-11 01:21:19 QQ: 'select v6531 from c10' 2019-02-11 01:21:19 II: Finished in 0.08s 2019-02-11 01:50:24 QQ: 'SELECT 1' 2019-02-11 01:50:25 II: Finished in 0.89s 2019-02-11 01:50:25 QQ: 'select v6531 from c10' 2019-02-11 01:50:44 II: Finished in 19.1s 2019-02-11 01:55:00 2.5% 97.5% 2019-02-11 01:55:00 nmorpob6 0.365 NA NA 2019-02-11 01:55:00 2019-02-11 01:55:00 > svyttest(v6033 ~ nmorpob6, censo_design) 2019-02-11 01:55:21 QQ: 'SELECT 1' 2019-02-11 01:55:21 II: Finished in 0s 2019-02-11 01:55:21 QQ: 'select v6033, v6531 from c10' 2019-02-11 01:55:22 II: Finished in 1.07s 2019-02-11 02:17:09 2019-02-11 02:17:09 Design-based t-test 2019-02-11 02:17:09 2019-02-11 02:17:09 data: v6033 ~ nmorpob6 2019-02-11 02:17:09 t = 9.6246, df = 78, p-value = 6.667e-15 2019-02-11 02:17:09 alternative hypothesis: true difference in mean is not equal to 0 2019-02-11 02:17:09 95 percent confidence interval: 2019-02-11 02:17:09 0.4579258 0.6921233 2019-02-11 02:17:09 sample estimates: 2019-02-11 02:17:09 difference in mean 2019-02-11 02:17:09 0.5750246 2019-02-11 02:17:09 2019-02-11 02:17:09 2019-02-11 02:17:09 > svychisq(~nmorpob6 + sexo, censo_design) 2019-02-11 02:17:09 QQ: 'SELECT 1' 2019-02-11 02:17:09 II: Finished in 0s 2019-02-11 02:17:09 QQ: 'select v6531, v0601 from c10' 2019-02-11 02:17:16 II: Finished in 6.87s 2019-02-11 02:17:34 QQ: 'SELECT 1' 2019-02-11 02:17:35 II: Finished in 0.22s 2019-02-11 02:17:35 QQ: 'select v6531, v0601 from c10' 2019-02-11 02:17:35 II: Finished in 0.25s 2019-02-11 02:17:54 QQ: 'SELECT 1' 2019-02-11 02:17:54 II: Finished in 0s 2019-02-11 02:22:22 QQ: 'SELECT 1' 2019-02-11 02:22:22 II: Finished in 0s 2019-02-11 02:22:22 QQ: 'select v6531, v0601 from c10' 2019-02-11 02:22:22 II: Finished in 0.17s 2019-02-11 02:22:41 2019-02-11 02:22:41 Pearson's X^2: Rao & Scott adjustment 2019-02-11 02:22:41 2019-02-11 02:22:41 data: NextMethod("svychisq", design) 2019-02-11 02:22:41 F = 132.86, ndf = 1, ddf = 79, p-value < 2.2e-16 2019-02-11 02:22:41 2019-02-11 02:22:41 2019-02-11 02:22:41 > glm_result <- svyglm(v6033 ~ nmorpob6 + sexo, censo_design) 2019-02-11 02:23:01 QQ: 'SELECT 1' 2019-02-11 02:23:01 II: Finished in 0s 2019-02-11 02:23:01 QQ: 'select v6033, v6531, v0601 from c10' 2019-02-11 02:23:01 II: Finished in 0.19s 2019-02-11 02:48:16 2019-02-11 02:48:16 > summary(glm_result) 2019-02-11 02:48:21 2019-02-11 02:48:21 Call: 2019-02-11 02:48:21 NextMethod(formula = "svyglm", design) 2019-02-11 02:48:21 2019-02-11 02:48:21 Survey design: 2019-02-11 02:48:21 survey::svrepdesign(weight = as.formula(paste0("~", unique_designs[i, 2019-02-11 02:48:21 "type"], "_wgt")), repweights = bootw$repweights, type = "bootstrap", 2019-02-11 02:48:21 combined.weights = FALSE, scale = bootw$scale, rscales = bootw$rscales, 2019-02-11 02:48:21 data = paste0("c", substr(unique_designs[i, "year"], 3, 4), 2019-02-11 02:48:21 ifelse(unique_designs[i, "type"] == "pes", "", paste0("_", 2019-02-11 02:48:21 unique_designs[i, "type"]))), dbtype = "MonetDBLite", 2019-02-11 02:48:21 dbname = unique_designs[i, "dbfolder"]) 2019-02-11 02:48:21 2019-02-11 02:48:21 Coefficients: 2019-02-11 02:48:21 Estimate Std. Error t value Pr(>|t|) 2019-02-11 02:48:21 (Intercept) 44.06560 0.03955 1114.290 < 2e-16 *** 2019-02-11 02:48:21 nmorpob6 0.57361 0.05976 9.598 8.50e-15 *** 2019-02-11 02:48:21 sexofeminino 0.51847 0.05765 8.994 1.23e-13 *** 2019-02-11 02:48:21 --- 2019-02-11 02:48:21 Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 2019-02-11 02:48:21 2019-02-11 02:48:21 (Dispersion parameter for gaussian family taken to be 230099349638) 2019-02-11 02:48:21 2019-02-11 02:48:21 Number of Fisher Scoring iterations: 2 2019-02-11 02:48:21 2019-02-11 02:48:21 2019-02-11 02:48:21 > library(convey) 2019-02-11 02:48:27 2019-02-11 02:48:27 > censo_design <- convey_prep(censo_design) 2019-02-11 02:48:27 2019-02-11 02:48:27 > sub_censo_design <- subset(censo_design, v6531 >= 2019-02-11 02:48:27 + 0) 2019-02-11 02:48:27 QQ: 'SELECT 1' 2019-02-11 02:48:39 II: Finished in 11.95s 2019-02-11 02:48:39 QQ: 'select v6531 from c10' 2019-02-11 02:48:39 II: Finished in 0.11s 2019-02-11 02:52:24 2019-02-11 02:52:24 > svygini(~v6531, sub_censo_design, na.rm = TRUE) 2019-02-11 02:52:24 QQ: 'SELECT 1' 2019-02-11 02:52:24 II: Finished in 0s 2019-02-11 02:52:24 QQ: 'select v6531 from c10' 2019-02-11 02:52:25 II: Finished in 0.1s 2019-02-11 02:52:25 QQ: 'SELECT 1' 2019-02-11 02:52:25 II: Finished in 0s 2019-02-11 02:52:25 QQ: 'select v6531 from c10' 2019-02-11 02:52:25 II: Finished in 0.1s 2019-02-11 03:01:55 gini SE 2019-02-11 03:01:55 v6531 0.61061 6e-04 2019-02-11 03:01:55 2019-02-11 03:01:55 > close(censo_design, shutdown = TRUE) 2019-02-11 03:02:04 > test return code=0