2019-02-09 22:38:50 2019-02-09 22:38:50 R version 3.5.1 (2018-07-02) -- "Feather Spray" 2019-02-09 22:38:50 Copyright (C) 2018 The R Foundation for Statistical Computing 2019-02-09 22:38:50 Platform: x86_64-pc-linux-gnu (64-bit) 2019-02-09 22:38:50 2019-02-09 22:38:50 R is free software and comes with ABSOLUTELY NO WARRANTY. 2019-02-09 22:38:50 You are welcome to redistribute it under certain conditions. 2019-02-09 22:38:50 Type 'license()' or 'licence()' for distribution details. 2019-02-09 22:38:50 2019-02-09 22:38:50 Natural language support but running in an English locale 2019-02-09 22:38:50 2019-02-09 22:38:50 R is a collaborative project with many contributors. 2019-02-09 22:38:50 Type 'contributors()' for more information and 2019-02-09 22:38:50 'citation()' on how to cite R or R packages in publications. 2019-02-09 22:38:50 2019-02-09 22:38:50 Type 'demo()' for some demos, 'help()' for on-line help, or 2019-02-09 22:38:50 'help.start()' for an HTML browser interface to help. 2019-02-09 22:38:50 Type 'q()' to quit R. 2019-02-09 22:38:50 2019-02-09 22:38:50 > setwd( Sys.getenv( "RWD" ) ) 2019-02-09 22:38:50 > a <- lodown::get_catalog("censo") 2019-02-09 22:38:50 building catalog for censo 2019-02-09 22:38:50 2019-02-09 22:38:58 > # don't do 2000 it's been broken forever 2019-02-09 22:38:58 > lodown::lodown("censo", catalog=a[a$year == 2010,], output_dir= getwd()) 2019-02-09 22:38:58 locally downloading censo 2019-02-09 22:38:58 2019-02-09 22:39:03 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/AC.zip' 2019-02-09 22:39:03 cached in 2019-02-09 22:39:03 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/8d33c41dcfde91034b1afbc3105bd061.Rcache' 2019-02-09 22:39:03 copying to 2019-02-09 22:39:03 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpYnyNrl/file7df27ade422a' 2019-02-09 22:39:03 2019-02-09 22:39:27 censo catalog entry 1 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296/MonetDB' 2019-02-09 22:39:27 2019-02-09 22:45:44 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/AL.zip' 2019-02-09 22:45:44 cached in 2019-02-09 22:45:44 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/675d0405924a1b73a6f889f953a759ab.Rcache' 2019-02-09 22:45:44 copying to 2019-02-09 22:45:44 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpYnyNrl/file7df27ade422a' 2019-02-09 22:45:44 2019-02-09 22:48:24 censo catalog entry 2 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296/MonetDB' 2019-02-09 22:48:24 2019-02-09 22:50:47 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/AM.zip' 2019-02-09 22:50:47 cached in 2019-02-09 22:50:47 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/8a1e7a9111551585f7cec0b7b767e0c7.Rcache' 2019-02-09 22:50:47 copying to 2019-02-09 22:50:47 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpYnyNrl/file7df27ade422a' 2019-02-09 22:50:47 2019-02-09 22:53:09 censo catalog entry 3 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296/MonetDB' 2019-02-09 22:53:09 2019-02-09 22:54:02 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/AP.zip' 2019-02-09 22:54:02 cached in 2019-02-09 22:54:02 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/6eeff2ce0144bb14d5a56c6ca27fcdf9.Rcache' 2019-02-09 22:54:02 copying to 2019-02-09 22:54:02 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpYnyNrl/file7df27ade422a' 2019-02-09 22:54:02 2019-02-09 22:54:37 censo catalog entry 4 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296/MonetDB' 2019-02-09 22:54:37 2019-02-09 22:58:26 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/BA.zip' 2019-02-09 22:58:26 cached in 2019-02-09 22:58:26 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/f12488e852651d05e153bb9f21b670ed.Rcache' 2019-02-09 22:58:26 copying to 2019-02-09 22:58:26 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpYnyNrl/file7df27ade422a' 2019-02-09 22:58:26 2019-02-09 23:05:30 censo catalog entry 5 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296/MonetDB' 2019-02-09 23:05:30 2019-02-09 23:06:28 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/CE.zip' 2019-02-09 23:06:28 cached in 2019-02-09 23:06:28 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/6e5d97ea080321a3f736da278ccb0c36.Rcache' 2019-02-09 23:06:28 copying to 2019-02-09 23:06:28 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpYnyNrl/file7df27ade422a' 2019-02-09 23:06:28 2019-02-09 23:12:53 censo catalog entry 6 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296/MonetDB' 2019-02-09 23:12:53 2019-02-09 23:14:29 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/DF.zip' 2019-02-09 23:14:29 cached in 2019-02-09 23:14:29 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/31c64b57fe5442cb7c07b351e8c5a51c.Rcache' 2019-02-09 23:14:29 copying to 2019-02-09 23:14:29 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpYnyNrl/file7df27ade422a' 2019-02-09 23:14:29 2019-02-09 23:15:02 censo catalog entry 7 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296/MonetDB' 2019-02-09 23:15:02 2019-02-09 23:22:23 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/ES.zip' 2019-02-09 23:22:23 cached in 2019-02-09 23:22:23 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/b751b8a9e5ee7aa58c52b86c25bd041e.Rcache' 2019-02-09 23:22:23 copying to 2019-02-09 23:22:23 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpYnyNrl/file7df27ade422a' 2019-02-09 23:22:23 2019-02-09 23:26:50 censo catalog entry 8 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296/MonetDB' 2019-02-09 23:26:50 2019-02-09 23:32:11 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/GO.zip' 2019-02-09 23:32:11 cached in 2019-02-09 23:32:11 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/f29a3850a4b737df7e2e8ea62f0007b9.Rcache' 2019-02-09 23:32:11 copying to 2019-02-09 23:32:11 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpYnyNrl/file7df27ade422a' 2019-02-09 23:32:11 2019-02-09 23:35:57 censo catalog entry 9 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296/MonetDB' 2019-02-09 23:35:57 2019-02-09 23:36:38 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/MA.zip' 2019-02-09 23:36:38 cached in 2019-02-09 23:36:38 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/362a6e810463c8a0e38517f5163cc222.Rcache' 2019-02-09 23:36:38 copying to 2019-02-09 23:36:38 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpYnyNrl/file7df27ade422a' 2019-02-09 23:36:38 2019-02-09 23:39:56 censo catalog entry 10 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296/MonetDB' 2019-02-09 23:39:56 2019-02-09 23:40:43 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/MG.zip' 2019-02-09 23:40:43 cached in 2019-02-09 23:40:43 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/90c71c4f917ad6d89d0f453c2e3c2dc9.Rcache' 2019-02-09 23:40:43 copying to 2019-02-09 23:40:43 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpYnyNrl/file7df27ade422a' 2019-02-09 23:40:43 2019-02-09 23:46:50 censo catalog entry 11 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296/MonetDB' 2019-02-09 23:46:50 2019-02-09 23:47:39 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/MS.zip' 2019-02-09 23:47:39 cached in 2019-02-09 23:47:39 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/b5e5b1b9e2e979e74c9ec72feec10865.Rcache' 2019-02-09 23:47:39 copying to 2019-02-09 23:47:39 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpYnyNrl/file7df27ade422a' 2019-02-09 23:47:39 2019-02-09 23:50:05 censo catalog entry 12 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296/MonetDB' 2019-02-09 23:50:05 2019-02-09 23:51:22 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/MT.zip' 2019-02-09 23:51:22 cached in 2019-02-09 23:51:22 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/86f0b09d2b55f9efa586af32e4f2314a.Rcache' 2019-02-09 23:51:22 copying to 2019-02-09 23:51:22 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpYnyNrl/file7df27ade422a' 2019-02-09 23:51:22 2019-02-09 23:53:57 censo catalog entry 13 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296/MonetDB' 2019-02-09 23:53:57 2019-02-09 23:55:50 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/PA.zip' 2019-02-09 23:55:50 cached in 2019-02-09 23:55:50 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/738b3f4e5c93d2280a8b0a744134c648.Rcache' 2019-02-09 23:55:50 copying to 2019-02-09 23:55:50 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpYnyNrl/file7df27ade422a' 2019-02-09 23:55:50 2019-02-10 00:00:56 censo catalog entry 14 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296/MonetDB' 2019-02-10 00:00:56 2019-02-10 00:02:23 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/PB.zip' 2019-02-10 00:02:23 cached in 2019-02-10 00:02:23 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/8bd47199975bdf2964c09aa4e21648e1.Rcache' 2019-02-10 00:02:23 copying to 2019-02-10 00:02:23 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpYnyNrl/file7df27ade422a' 2019-02-10 00:02:23 2019-02-10 00:07:22 censo catalog entry 15 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296/MonetDB' 2019-02-10 00:07:22 2019-02-10 00:08:37 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/PE.zip' 2019-02-10 00:08:37 cached in 2019-02-10 00:08:37 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/eac1739962da73a00dfb693f03377c92.Rcache' 2019-02-10 00:08:37 copying to 2019-02-10 00:08:37 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpYnyNrl/file7df27ade422a' 2019-02-10 00:08:37 2019-02-10 00:11:25 censo catalog entry 16 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296/MonetDB' 2019-02-10 00:11:25 2019-02-10 00:12:29 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/PI.zip' 2019-02-10 00:12:29 cached in 2019-02-10 00:12:29 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/06c1460710d6b2b70933afe955bf06ee.Rcache' 2019-02-10 00:12:29 copying to 2019-02-10 00:12:29 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpYnyNrl/file7df27ade422a' 2019-02-10 00:12:29 2019-02-10 00:14:44 censo catalog entry 17 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296/MonetDB' 2019-02-10 00:14:44 2019-02-10 00:15:32 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/PR.zip' 2019-02-10 00:15:32 cached in 2019-02-10 00:15:32 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/409a9525b7a91b4618baf65cc89dce07.Rcache' 2019-02-10 00:15:32 copying to 2019-02-10 00:15:32 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpYnyNrl/file7df27ade422a' 2019-02-10 00:15:32 2019-02-10 00:17:55 censo catalog entry 18 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296/MonetDB' 2019-02-10 00:17:55 2019-02-10 00:19:15 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/RJ.zip' 2019-02-10 00:19:15 cached in 2019-02-10 00:19:15 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/5b82d082ec19bfb478942334dee06362.Rcache' 2019-02-10 00:19:15 copying to 2019-02-10 00:19:15 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpYnyNrl/file7df27ade422a' 2019-02-10 00:19:15 2019-02-10 00:21:59 censo catalog entry 19 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296/MonetDB' 2019-02-10 00:21:59 2019-02-10 00:22:37 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/RN.zip' 2019-02-10 00:22:37 cached in 2019-02-10 00:22:37 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/791786e4d34a82d9602a9782cfcf56ee.Rcache' 2019-02-10 00:22:37 copying to 2019-02-10 00:22:37 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpYnyNrl/file7df27ade422a' 2019-02-10 00:22:37 2019-02-10 00:24:54 censo catalog entry 20 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296/MonetDB' 2019-02-10 00:24:54 2019-02-10 00:27:54 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/RO.zip' 2019-02-10 00:27:54 cached in 2019-02-10 00:27:54 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/d1e8db0e4c49bf7785e6765a73a0ef97.Rcache' 2019-02-10 00:27:54 copying to 2019-02-10 00:27:54 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpYnyNrl/file7df27ade422a' 2019-02-10 00:27:54 2019-02-10 00:30:17 censo catalog entry 21 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296/MonetDB' 2019-02-10 00:30:17 2019-02-10 00:32:18 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/RR.zip' 2019-02-10 00:32:18 cached in 2019-02-10 00:32:18 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/30da4639719883b3e680399fe5f3f7c5.Rcache' 2019-02-10 00:32:18 copying to 2019-02-10 00:32:18 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpYnyNrl/file7df27ade422a' 2019-02-10 00:32:18 2019-02-10 00:32:27 censo catalog entry 22 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296/MonetDB' 2019-02-10 00:32:27 2019-02-10 00:35:10 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/RS.zip' 2019-02-10 00:35:10 cached in 2019-02-10 00:35:10 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/989abcab6ef8f4cc0482c4da694d254e.Rcache' 2019-02-10 00:35:10 copying to 2019-02-10 00:35:10 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpYnyNrl/file7df27ade422a' 2019-02-10 00:35:10 2019-02-10 00:37:38 censo catalog entry 23 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296/MonetDB' 2019-02-10 00:37:38 2019-02-10 00:38:47 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/SC.zip' 2019-02-10 00:38:47 cached in 2019-02-10 00:38:47 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/5aa8eea1b7368218b7503d61f196b586.Rcache' 2019-02-10 00:38:47 copying to 2019-02-10 00:38:47 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpYnyNrl/file7df27ade422a' 2019-02-10 00:38:47 2019-02-10 00:42:48 censo catalog entry 24 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296/MonetDB' 2019-02-10 00:42:48 2019-02-10 00:44:09 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/SE.zip' 2019-02-10 00:44:09 cached in 2019-02-10 00:44:09 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/af4222637a1c8e705f816d7a78284a2f.Rcache' 2019-02-10 00:44:09 copying to 2019-02-10 00:44:09 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpYnyNrl/file7df27ade422a' 2019-02-10 00:44:09 2019-02-10 00:46:19 censo catalog entry 25 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296/MonetDB' 2019-02-10 00:46:19 2019-02-10 00:47:55 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/SP1.zip' 2019-02-10 00:47:55 cached in 2019-02-10 00:47:55 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/5493bb945da3b02e07808de8b2c38054.Rcache' 2019-02-10 00:47:55 copying to 2019-02-10 00:47:55 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpYnyNrl/file7df27ade422a' 2019-02-10 00:47:55 2019-02-10 00:53:45 censo catalog entry 26 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296/MonetDB' 2019-02-10 00:53:45 2019-02-10 00:55:07 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/SP2_RM.zip' 2019-02-10 00:55:07 cached in 2019-02-10 00:55:07 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/688c1a930ab09e425507f8e308e0d3cc.Rcache' 2019-02-10 00:55:07 copying to 2019-02-10 00:55:07 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpYnyNrl/file7df27ade422a' 2019-02-10 00:55:07 2019-02-10 00:57:35 censo catalog entry 27 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296/MonetDB' 2019-02-10 00:57:35 2019-02-10 00:58:52 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/TO.zip' 2019-02-10 00:58:52 cached in 2019-02-10 00:58:52 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/319c75b43a1d30166e3a0185c3a7d1ad.Rcache' 2019-02-10 00:58:52 copying to 2019-02-10 00:58:52 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpYnyNrl/file7df27ade422a' 2019-02-10 00:58:52 2019-02-10 01:00:25 censo catalog entry 28 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296/MonetDB' 2019-02-10 01:00:25 2019-02-10 01:48:12 censo survey design entry 1 of 2 stored at '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296/dom 2010 design.rds' 2019-02-10 01:48:12 2019-02-10 03:26:31 censo survey design entry 2 of 2 stored at '/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296/pes 2010 design.rds' 2019-02-10 03:26:31 2019-02-10 03:26:31 censo local download completed 2019-02-10 03:26:31 2019-02-10 03:26:31 Warning message: 2019-02-10 03:26:31 In .Internal(gc(verbose, reset, full)) : 2019-02-10 03:26:31 Connection is garbage-collected, use dbDisconnect() to avoid this. 2019-02-10 03:26:31 > setup return code=0 2019-02-10 03:26:32 2019-02-10 03:26:32 R version 3.5.1 (2018-07-02) -- "Feather Spray" 2019-02-10 03:26:32 Copyright (C) 2018 The R Foundation for Statistical Computing 2019-02-10 03:26:32 Platform: x86_64-pc-linux-gnu (64-bit) 2019-02-10 03:26:32 2019-02-10 03:26:32 R is free software and comes with ABSOLUTELY NO WARRANTY. 2019-02-10 03:26:32 You are welcome to redistribute it under certain conditions. 2019-02-10 03:26:32 Type 'license()' or 'licence()' for distribution details. 2019-02-10 03:26:32 2019-02-10 03:26:32 Natural language support but running in an English locale 2019-02-10 03:26:32 2019-02-10 03:26:32 R is a collaborative project with many contributors. 2019-02-10 03:26:32 Type 'contributors()' for more information and 2019-02-10 03:26:32 'citation()' on how to cite R or R packages in publications. 2019-02-10 03:26:32 2019-02-10 03:26:32 Type 'demo()' for some demos, 'help()' for on-line help, or 2019-02-10 03:26:32 'help.start()' for an HTML browser interface to help. 2019-02-10 03:26:32 Type 'q()' to quit R. 2019-02-10 03:26:32 2019-02-10 03:26:32 > setwd( Sys.getenv( "RWD" ) ) 2019-02-10 03:26:32 > 2019-02-10 03:26:32 > machine_specific_replacements <- 2019-02-10 03:26:32 + list( 2019-02-10 03:26:32 + 2019-02-10 03:26:32 + # replace the folder path on macnix 2019-02-10 03:26:32 + c( 'path.expand( \"~\" ) , \"CENSO\"' , paste0( '"' , getwd() , '"' ) ) , 2019-02-10 03:26:32 + 2019-02-10 03:26:32 + # change other things in the script to be run 2019-02-10 03:26:32 + c( "hello" , "howdy" ) 2019-02-10 03:26:32 + 2019-02-10 03:26:32 + ) 2019-02-10 03:26:32 > 2019-02-10 03:26:32 > source( lodown::syntaxtractor( "censo" , replacements = machine_specific_replacements , setup_test = "test" ) , echo = TRUE ) 2019-02-10 03:26:33 2019-02-10 03:26:33 > library(lodown) 2019-02-10 03:26:33 2019-02-10 03:26:33 > censo_cat <- get_catalog("censo", output_dir = file.path("/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296")) 2019-02-10 03:26:33 building catalog for censo 2019-02-10 03:26:33 2019-02-10 03:26:40 2019-02-10 03:26:40 > censo_cat <- subset(censo_cat, year == 2010) 2019-02-10 03:26:40 2019-02-10 03:26:40 > stopifnot(nrow(censo_cat) > 0) 2019-02-10 03:26:40 2019-02-10 03:26:40 > library(DBI) 2019-02-10 03:26:40 2019-02-10 03:26:40 > library(MonetDBLite) 2019-02-10 03:26:43 2019-02-10 03:26:43 > library(survey) 2019-02-10 03:26:43 Loading required package: grid 2019-02-10 03:26:43 Loading required package: Matrix 2019-02-10 03:26:45 Loading required package: survival 2019-02-10 03:26:46 2019-02-10 03:26:46 Attaching package: ‘survey’ 2019-02-10 03:26:46 2019-02-10 03:26:46 The following object is masked from ‘package:graphics’: 2019-02-10 03:26:46 2019-02-10 03:26:46 dotchart 2019-02-10 03:26:46 2019-02-10 03:26:46 2019-02-10 03:26:46 > options(survey.lonely.psu = "adjust") 2019-02-10 03:26:46 2019-02-10 03:26:46 > censo_design <- readRDS(file.path("/export/scratch1/home/hannes/eanthony/r-wd/censo-1549748296", 2019-02-10 03:26:46 + "pes 2010 design.rds")) 2019-02-10 03:27:10 2019-02-10 03:27:10 > censo_design <- open(censo_design, driver = MonetDBLite()) 2019-02-10 03:27:43 2019-02-10 03:27:43 > censo_design <- update(censo_design, nmorpob1 = ifelse(v6531 >= 2019-02-10 03:27:43 + 0, as.numeric(v6531 < 70), NA), nmorpob2 = ifelse(v6531 >= 2019-02-10 03:27:43 + 0, as.numer .... [TRUNCATED] 2019-02-10 03:27:43 2019-02-10 03:27:43 > sum(weights(censo_design, "sampling") != 0) 2019-02-10 03:27:43 [1] 20635472 2019-02-10 03:27:43 2019-02-10 03:27:43 > svyby(~one, ~state_name, censo_design, unwtd.count) 2019-02-10 03:27:43 QQ: 'SELECT 1' 2019-02-10 03:27:43 II: Finished in 0s 2019-02-10 03:27:43 QQ: 'select one from c10' 2019-02-10 03:27:43 II: Finished in 0s 2019-02-10 03:27:43 QQ: 'SELECT 1' 2019-02-10 03:27:43 II: Finished in 0s 2019-02-10 03:27:43 QQ: 'select v0001 from c10' 2019-02-10 03:27:43 II: Finished in 0.24s 2019-02-10 03:31:24 state_name counts se 2019-02-10 03:31:24 Rondonia Rondonia 195607 0 2019-02-10 03:31:24 Acre Acre 93675 0 2019-02-10 03:31:24 Amazonas Amazonas 295034 0 2019-02-10 03:31:24 Roraima Roraima 63765 0 2019-02-10 03:31:24 Para Para 729094 0 2019-02-10 03:31:24 Amapa Amapa 78344 0 2019-02-10 03:31:24 Tocantins Tocantins 267745 0 2019-02-10 03:31:24 Maranhao Maranhao 793241 0 2019-02-10 03:31:24 Piaui Piaui 496477 0 2019-02-10 03:31:24 Ceara Ceara 846164 0 2019-02-10 03:31:24 Rio Grande do Norte Rio Grande do Norte 424586 0 2019-02-10 03:31:24 Paraiba Paraiba 571631 0 2019-02-10 03:31:24 Pernambuco Pernambuco 892250 0 2019-02-10 03:31:24 Alagoas Alagoas 349966 0 2019-02-10 03:31:24 Sergipe Sergipe 245354 0 2019-02-10 03:31:24 Bahia Bahia 1550842 0 2019-02-10 03:31:24 Minas Gerais Minas Gerais 2506265 0 2019-02-10 03:31:24 Espirito Santo Espirito Santo 400130 0 2019-02-10 03:31:24 Rio de Janeiro Rio de Janeiro 1143650 0 2019-02-10 03:31:24 Sao Paulo Sao Paulo 3651181 0 2019-02-10 03:31:24 Parana Parana 1293034 0 2019-02-10 03:31:24 Santa Catarina Santa Catarina 872242 0 2019-02-10 03:31:24 Rio Grande do Sul Rio Grande do Sul 1388443 0 2019-02-10 03:31:24 Mato Grosso do Sul Mato Grosso do Sul 276714 0 2019-02-10 03:31:24 Mato Grosso Mato Grosso 386537 0 2019-02-10 03:31:24 Goias Goias 707043 0 2019-02-10 03:31:24 Distrito Federal Distrito Federal 116458 0 2019-02-10 03:31:24 2019-02-10 03:31:24 > svytotal(~one, censo_design) 2019-02-10 03:31:24 QQ: 'SELECT 1' 2019-02-10 03:31:24 II: Finished in 0s 2019-02-10 03:31:24 QQ: 'select one from c10' 2019-02-10 03:31:24 II: Finished in 0s 2019-02-10 03:31:52 total SE 2019-02-10 03:31:52 one 190755799 48631 2019-02-10 03:31:52 2019-02-10 03:31:52 > svyby(~one, ~state_name, censo_design, svytotal) 2019-02-10 03:31:52 QQ: 'SELECT 1' 2019-02-10 03:31:52 II: Finished in 0s 2019-02-10 03:31:52 QQ: 'select one from c10' 2019-02-10 03:31:52 II: Finished in 0s 2019-02-10 03:31:52 QQ: 'SELECT 1' 2019-02-10 03:31:52 II: Finished in 0s 2019-02-10 03:31:52 QQ: 'select v0001 from c10' 2019-02-10 03:31:52 II: Finished in 0.19s 2019-02-10 03:35:28 state_name one se 2019-02-10 03:35:28 Rondonia Rondonia 1562409 3719.967 2019-02-10 03:35:28 Acre Acre 733559 2757.106 2019-02-10 03:35:28 Amazonas Amazonas 3483985 8991.012 2019-02-10 03:35:28 Roraima Roraima 450479 2891.608 2019-02-10 03:35:28 Para Para 7581051 12644.909 2019-02-10 03:35:28 Amapa Amapa 669526 2999.657 2019-02-10 03:35:28 Tocantins Tocantins 1383445 3750.690 2019-02-10 03:35:28 Maranhao Maranhao 6574789 8619.443 2019-02-10 03:35:28 Piaui Piaui 3118360 5245.320 2019-02-10 03:35:28 Ceara Ceara 8452381 9851.486 2019-02-10 03:35:28 Rio Grande do Norte Rio Grande do Norte 3168027 6582.152 2019-02-10 03:35:28 Paraiba Paraiba 3766528 5901.976 2019-02-10 03:35:28 Pernambuco Pernambuco 8796448 9281.228 2019-02-10 03:35:28 Alagoas Alagoas 3120494 6469.788 2019-02-10 03:35:28 Sergipe Sergipe 2068017 5097.413 2019-02-10 03:35:28 Bahia Bahia 14016906 12148.316 2019-02-10 03:35:28 Minas Gerais Minas Gerais 19597330 15101.868 2019-02-10 03:35:28 Espirito Santo Espirito Santo 3514952 5462.700 2019-02-10 03:35:28 Rio de Janeiro Rio de Janeiro 15989929 17378.944 2019-02-10 03:35:28 Sao Paulo Sao Paulo 41262199 24184.481 2019-02-10 03:35:28 Parana Parana 10444526 10148.200 2019-02-10 03:35:28 Santa Catarina Santa Catarina 6248436 7512.355 2019-02-10 03:35:28 Rio Grande do Sul Rio Grande do Sul 10693929 9771.474 2019-02-10 03:35:28 Mato Grosso do Sul Mato Grosso do Sul 2449024 4996.874 2019-02-10 03:35:28 Mato Grosso Mato Grosso 3035122 6375.055 2019-02-10 03:35:28 Goias Goias 6003788 8419.415 2019-02-10 03:35:28 Distrito Federal Distrito Federal 2570160 7158.087 2019-02-10 03:35:28 2019-02-10 03:35:28 > svymean(~v6033, censo_design) 2019-02-10 03:35:28 QQ: 'SELECT 1' 2019-02-10 03:35:28 II: Finished in 0s 2019-02-10 03:35:28 QQ: 'select v6033 from c10' 2019-02-10 03:35:28 II: Finished in 0s 2019-02-10 03:36:01 mean SE 2019-02-10 03:36:01 v6033 44.532 0.0232 2019-02-10 03:36:01 2019-02-10 03:36:01 > svyby(~v6033, ~state_name, censo_design, svymean) 2019-02-10 03:36:01 QQ: 'SELECT 1' 2019-02-10 03:36:01 II: Finished in 0s 2019-02-10 03:36:01 QQ: 'select v6033 from c10' 2019-02-10 03:36:01 II: Finished in 0s 2019-02-10 03:36:01 QQ: 'SELECT 1' 2019-02-10 03:36:01 II: Finished in 0s 2019-02-10 03:36:01 QQ: 'select v0001 from c10' 2019-02-10 03:36:01 II: Finished in 0.19s 2019-02-10 03:39:46 state_name v6033 se 2019-02-10 03:39:46 Rondonia Rondonia 43.47609 0.25259651 2019-02-10 03:39:46 Acre Acre 44.14539 0.34838929 2019-02-10 03:39:46 Amazonas Amazonas 44.89294 0.25082099 2019-02-10 03:39:46 Roraima Roraima 44.61115 0.54022560 2019-02-10 03:39:46 Para Para 44.06793 0.14907603 2019-02-10 03:39:46 Amapa Amapa 44.36371 0.48361606 2019-02-10 03:39:46 Tocantins Tocantins 44.08827 0.25247971 2019-02-10 03:39:46 Maranhao Maranhao 44.39162 0.14310705 2019-02-10 03:39:46 Piaui Piaui 44.23805 0.23085797 2019-02-10 03:39:46 Ceara Ceara 43.97193 0.11920061 2019-02-10 03:39:46 Rio Grande do Norte Rio Grande do Norte 44.05621 0.17674503 2019-02-10 03:39:46 Paraiba Paraiba 45.40817 0.17917689 2019-02-10 03:39:46 Pernambuco Pernambuco 44.35515 0.10696337 2019-02-10 03:39:46 Alagoas Alagoas 44.39060 0.24325208 2019-02-10 03:39:46 Sergipe Sergipe 43.67018 0.22993718 2019-02-10 03:39:46 Bahia Bahia 44.00062 0.10093140 2019-02-10 03:39:46 Minas Gerais Minas Gerais 44.22639 0.08020715 2019-02-10 03:39:46 Espirito Santo Espirito Santo 44.43069 0.14881886 2019-02-10 03:39:46 Rio de Janeiro Rio de Janeiro 45.11529 0.10910060 2019-02-10 03:39:46 Sao Paulo Sao Paulo 44.86147 0.05927714 2019-02-10 03:39:46 Parana Parana 44.88411 0.10775573 2019-02-10 03:39:46 Santa Catarina Santa Catarina 44.42404 0.12003968 2019-02-10 03:39:46 Rio Grande do Sul Rio Grande do Sul 45.18820 0.09892450 2019-02-10 03:39:46 Mato Grosso do Sul Mato Grosso do Sul 45.08575 0.23417139 2019-02-10 03:39:46 Mato Grosso Mato Grosso 43.70309 0.23512605 2019-02-10 03:39:46 Goias Goias 44.16120 0.16123461 2019-02-10 03:39:46 Distrito Federal Distrito Federal 43.61118 0.34381452 2019-02-10 03:39:46 2019-02-10 03:39:46 > svymean(~sexo, censo_design) 2019-02-10 03:39:46 QQ: 'SELECT 1' 2019-02-10 03:39:46 II: Finished in 0s 2019-02-10 03:39:46 QQ: 'select v0601 from c10' 2019-02-10 03:39:47 II: Finished in 0.36s 2019-02-10 03:40:21 mean SE 2019-02-10 03:40:21 sexomasculino 0.48967 1e-04 2019-02-10 03:40:21 sexofeminino 0.51033 1e-04 2019-02-10 03:40:21 2019-02-10 03:40:21 > svyby(~sexo, ~state_name, censo_design, svymean) 2019-02-10 03:40:21 QQ: 'SELECT 1' 2019-02-10 03:40:21 II: Finished in 0s 2019-02-10 03:40:21 QQ: 'select v0601 from c10' 2019-02-10 03:40:21 II: Finished in 0.11s 2019-02-10 03:40:22 QQ: 'SELECT 1' 2019-02-10 03:40:22 II: Finished in 0s 2019-02-10 03:40:22 QQ: 'select v0001 from c10' 2019-02-10 03:40:22 II: Finished in 0.14s 2019-02-10 03:44:19 state_name sexomasculino sexofeminino se1 2019-02-10 03:44:19 Rondonia Rondonia 0.5089301 0.4910699 0.0009208707 2019-02-10 03:44:19 Acre Acre 0.5021055 0.4978945 0.0011846030 2019-02-10 03:44:19 Amazonas Amazonas 0.5032108 0.4967892 0.0007731918 2019-02-10 03:44:19 Roraima Roraima 0.5080348 0.4919652 0.0017727458 2019-02-10 03:44:19 Para Para 0.5041302 0.4958698 0.0004785139 2019-02-10 03:44:19 Amapa Amapa 0.5005556 0.4994444 0.0014691412 2019-02-10 03:44:19 Tocantins Tocantins 0.5077354 0.4922646 0.0008282168 2019-02-10 03:44:19 Maranhao Maranhao 0.4960638 0.5039362 0.0005335229 2019-02-10 03:44:19 Piaui Piaui 0.4901365 0.5098635 0.0007026171 2019-02-10 03:44:19 Ceara Ceara 0.4874470 0.5125530 0.0005136485 2019-02-10 03:44:19 Rio Grande do Norte Rio Grande do Norte 0.4889122 0.5110878 0.0006285138 2019-02-10 03:44:19 Paraiba Paraiba 0.4843662 0.5156338 0.0005966141 2019-02-10 03:44:19 Pernambuco Pernambuco 0.4809533 0.5190467 0.0004862079 2019-02-10 03:44:19 Alagoas Alagoas 0.4844640 0.5155360 0.0007438779 2019-02-10 03:44:19 Sergipe Sergipe 0.4859926 0.5140074 0.0009133250 2019-02-10 03:44:19 Bahia Bahia 0.4907121 0.5092879 0.0003944567 2019-02-10 03:44:19 Minas Gerais Minas Gerais 0.4919995 0.5080005 0.0002632672 2019-02-10 03:44:19 Espirito Santo Espirito Santo 0.4925296 0.5074704 0.0005870076 2019-02-10 03:44:19 Rio de Janeiro Rio de Janeiro 0.4769051 0.5230949 0.0004141546 2019-02-10 03:44:19 Sao Paulo Sao Paulo 0.4865924 0.5134076 0.0002492302 2019-02-10 03:44:19 Parana Parana 0.4912615 0.5087385 0.0003676708 2019-02-10 03:44:19 Santa Catarina Santa Catarina 0.4961818 0.5038182 0.0003411992 2019-02-10 03:44:19 Rio Grande do Sul Rio Grande do Sul 0.4867301 0.5132699 0.0003629893 2019-02-10 03:44:19 Mato Grosso do Sul Mato Grosso do Sul 0.4981282 0.5018718 0.0008264108 2019-02-10 03:44:19 Mato Grosso Mato Grosso 0.5105350 0.4894650 0.0006293292 2019-02-10 03:44:19 Goias Goias 0.4966243 0.5033757 0.0005103873 2019-02-10 03:44:19 Distrito Federal Distrito Federal 0.4781337 0.5218663 0.0012820876 2019-02-10 03:44:19 se2 2019-02-10 03:44:19 Rondonia 0.0009208707 2019-02-10 03:44:19 Acre 0.0011846030 2019-02-10 03:44:19 Amazonas 0.0007731918 2019-02-10 03:44:19 Roraima 0.0017727458 2019-02-10 03:44:19 Para 0.0004785139 2019-02-10 03:44:19 Amapa 0.0014691412 2019-02-10 03:44:19 Tocantins 0.0008282168 2019-02-10 03:44:19 Maranhao 0.0005335229 2019-02-10 03:44:19 Piaui 0.0007026171 2019-02-10 03:44:19 Ceara 0.0005136485 2019-02-10 03:44:19 Rio Grande do Norte 0.0006285138 2019-02-10 03:44:19 Paraiba 0.0005966141 2019-02-10 03:44:19 Pernambuco 0.0004862079 2019-02-10 03:44:19 Alagoas 0.0007438779 2019-02-10 03:44:19 Sergipe 0.0009133250 2019-02-10 03:44:19 Bahia 0.0003944567 2019-02-10 03:44:19 Minas Gerais 0.0002632672 2019-02-10 03:44:19 Espirito Santo 0.0005870076 2019-02-10 03:44:19 Rio de Janeiro 0.0004141546 2019-02-10 03:44:19 Sao Paulo 0.0002492302 2019-02-10 03:44:19 Parana 0.0003676708 2019-02-10 03:44:19 Santa Catarina 0.0003411992 2019-02-10 03:44:19 Rio Grande do Sul 0.0003629893 2019-02-10 03:44:19 Mato Grosso do Sul 0.0008264108 2019-02-10 03:44:19 Mato Grosso 0.0006293292 2019-02-10 03:44:19 Goias 0.0005103873 2019-02-10 03:44:19 Distrito Federal 0.0012820876 2019-02-10 03:44:19 2019-02-10 03:44:19 > svytotal(~v6033, censo_design) 2019-02-10 03:44:19 QQ: 'SELECT 1' 2019-02-10 03:44:19 II: Finished in 0s 2019-02-10 03:44:19 QQ: 'select v6033 from c10' 2019-02-10 03:44:19 II: Finished in 0s 2019-02-10 03:44:36 total SE 2019-02-10 03:44:36 v6033 8494688084 4916921 2019-02-10 03:44:36 2019-02-10 03:44:36 > svyby(~v6033, ~state_name, censo_design, svytotal) 2019-02-10 03:44:36 QQ: 'SELECT 1' 2019-02-10 03:44:36 II: Finished in 0s 2019-02-10 03:44:36 QQ: 'select v6033 from c10' 2019-02-10 03:44:36 II: Finished in 0s 2019-02-10 03:44:36 QQ: 'SELECT 1' 2019-02-10 03:44:36 II: Finished in 0s 2019-02-10 03:44:36 QQ: 'select v0001 from c10' 2019-02-10 03:44:37 II: Finished in 0.18s 2019-02-10 03:48:12 state_name v6033 se 2019-02-10 03:48:12 Rondonia Rondonia 67927439 409898.9 2019-02-10 03:48:12 Acre Acre 32383247 259806.4 2019-02-10 03:48:12 Amazonas Amazonas 156406314 954704.2 2019-02-10 03:48:12 Roraima Roraima 20096387 295779.5 2019-02-10 03:48:12 Para Para 334081201 1292886.8 2019-02-10 03:48:12 Amapa Amapa 29702659 325123.4 2019-02-10 03:48:12 Tocantins Tocantins 60993702 392372.9 2019-02-10 03:48:12 Maranhao Maranhao 291865565 1019725.7 2019-02-10 03:48:12 Piaui Piaui 137950175 798110.0 2019-02-10 03:48:12 Ceara Ceara 371667509 1138292.4 2019-02-10 03:48:12 Rio Grande do Norte Rio Grande do Norte 139571251 633099.4 2019-02-10 03:48:12 Paraiba Paraiba 171031139 725915.2 2019-02-10 03:48:12 Pernambuco Pernambuco 390167775 992791.6 2019-02-10 03:48:12 Alagoas Alagoas 138520597 835652.7 2019-02-10 03:48:12 Sergipe Sergipe 90310670 495272.0 2019-02-10 03:48:12 Bahia Bahia 616752560 1388173.4 2019-02-10 03:48:12 Minas Gerais Minas Gerais 866719202 1628318.7 2019-02-10 03:48:12 Espirito Santo Espirito Santo 156171746 615126.0 2019-02-10 03:48:12 Rio de Janeiro Rio de Janeiro 721390292 1740986.3 2019-02-10 03:48:12 Sao Paulo Sao Paulo 1851082734 2542371.9 2019-02-10 03:48:12 Parana Parana 468793290 1169209.5 2019-02-10 03:48:12 Santa Catarina Santa Catarina 277580763 818593.1 2019-02-10 03:48:12 Rio Grande do Sul Rio Grande do Sul 483239360 1112804.5 2019-02-10 03:48:12 Mato Grosso do Sul Mato Grosso do Sul 110416076 598772.6 2019-02-10 03:48:12 Mato Grosso Mato Grosso 132644212 771537.8 2019-02-10 03:48:12 Goias Goias 265134506 994613.5 2019-02-10 03:48:12 Distrito Federal Distrito Federal 112087713 988768.5 2019-02-10 03:48:12 2019-02-10 03:48:12 > svytotal(~sexo, censo_design) 2019-02-10 03:48:12 QQ: 'SELECT 1' 2019-02-10 03:48:12 II: Finished in 0s 2019-02-10 03:48:12 QQ: 'select v0601 from c10' 2019-02-10 03:48:12 II: Finished in 0.11s 2019-02-10 03:48:38 total SE 2019-02-10 03:48:38 sexomasculino 93406990 29098 2019-02-10 03:48:38 sexofeminino 97348809 31977 2019-02-10 03:48:38 2019-02-10 03:48:38 > svyby(~sexo, ~state_name, censo_design, svytotal) 2019-02-10 03:48:38 QQ: 'SELECT 1' 2019-02-10 03:48:38 II: Finished in 0s 2019-02-10 03:48:38 QQ: 'select v0601 from c10' 2019-02-10 03:48:38 II: Finished in 0.11s 2019-02-10 03:48:39 QQ: 'SELECT 1' 2019-02-10 03:48:39 II: Finished in 0s 2019-02-10 03:48:39 QQ: 'select v0001 from c10' 2019-02-10 03:48:40 II: Finished in 0.14s 2019-02-10 03:52:14 state_name sexomasculino sexofeminino se1 2019-02-10 03:52:14 Rondonia Rondonia 795157 767252 2249.694 2019-02-10 03:52:14 Acre Acre 368324 365235 1650.162 2019-02-10 03:52:14 Amazonas Amazonas 1753179 1730806 5133.553 2019-02-10 03:52:14 Roraima Roraima 228859 221620 1567.469 2019-02-10 03:52:14 Para Para 3821837 3759214 6819.532 2019-02-10 03:52:14 Amapa Amapa 335135 334391 1870.399 2019-02-10 03:52:14 Tocantins Tocantins 702424 681021 2230.457 2019-02-10 03:52:14 Maranhao Maranhao 3261515 3313274 5396.426 2019-02-10 03:52:14 Piaui Piaui 1528422 1589938 3600.955 2019-02-10 03:52:14 Ceara Ceara 4120088 4332293 5710.404 2019-02-10 03:52:14 Rio Grande do Norte Rio Grande do Norte 1548887 1619140 3859.300 2019-02-10 03:52:14 Paraiba Paraiba 1824379 1942149 3864.370 2019-02-10 03:52:14 Pernambuco Pernambuco 4230681 4565767 5585.403 2019-02-10 03:52:14 Alagoas Alagoas 1511767 1608727 4077.794 2019-02-10 03:52:14 Sergipe Sergipe 1005041 1062976 3418.739 2019-02-10 03:52:14 Bahia Bahia 6878266 7138640 8366.462 2019-02-10 03:52:14 Minas Gerais Minas Gerais 9641877 9955453 9388.413 2019-02-10 03:52:14 Espirito Santo Espirito Santo 1731218 1783734 3250.786 2019-02-10 03:52:14 Rio de Janeiro Rio de Janeiro 7625679 8364250 10566.384 2019-02-10 03:52:14 Sao Paulo Sao Paulo 20077873 21184326 14744.699 2019-02-10 03:52:14 Parana Parana 5130994 5313532 6322.850 2019-02-10 03:52:14 Santa Catarina Santa Catarina 3100360 3148076 4352.285 2019-02-10 03:52:14 Rio Grande do Sul Rio Grande do Sul 5205057 5488872 6884.276 2019-02-10 03:52:14 Mato Grosso do Sul Mato Grosso do Sul 1219928 1229096 3231.225 2019-02-10 03:52:14 Mato Grosso Mato Grosso 1549536 1485586 3654.193 2019-02-10 03:52:14 Goias Goias 2981627 3022161 4850.740 2019-02-10 03:52:14 Distrito Federal Distrito Federal 1228880 1341280 5007.834 2019-02-10 03:52:14 se2 2019-02-10 03:52:14 Rondonia 2446.076 2019-02-10 03:52:14 Acre 1608.920 2019-02-10 03:52:14 Amazonas 5345.011 2019-02-10 03:52:14 Roraima 1728.515 2019-02-10 03:52:14 Para 7724.370 2019-02-10 03:52:14 Amapa 1714.910 2019-02-10 03:52:14 Tocantins 2164.314 2019-02-10 03:52:14 Maranhao 5714.810 2019-02-10 03:52:14 Piaui 3214.156 2019-02-10 03:52:14 Ceara 7357.290 2019-02-10 03:52:14 Rio Grande do Norte 3831.714 2019-02-10 03:52:14 Paraiba 3533.310 2019-02-10 03:52:14 Pernambuco 7004.359 2019-02-10 03:52:14 Alagoas 3875.065 2019-02-10 03:52:14 Sergipe 2886.588 2019-02-10 03:52:14 Bahia 8049.747 2019-02-10 03:52:14 Minas Gerais 8886.594 2019-02-10 03:52:14 Espirito Santo 3592.477 2019-02-10 03:52:14 Rio de Janeiro 11291.196 2019-02-10 03:52:14 Sao Paulo 16976.276 2019-02-10 03:52:14 Parana 6403.667 2019-02-10 03:52:14 Santa Catarina 4285.279 2019-02-10 03:52:14 Rio Grande do Sul 5475.887 2019-02-10 03:52:14 Mato Grosso do Sul 3199.682 2019-02-10 03:52:14 Mato Grosso 3774.778 2019-02-10 03:52:14 Goias 5545.421 2019-02-10 03:52:14 Distrito Federal 4699.140 2019-02-10 03:52:14 2019-02-10 03:52:14 > svyquantile(~v6033, censo_design, 0.5) 2019-02-10 03:52:14 QQ: 'SELECT 1' 2019-02-10 03:52:14 II: Finished in 0s 2019-02-10 03:52:14 QQ: 'select v6033 from c10' 2019-02-10 03:52:14 II: Finished in 0s 2019-02-10 03:52:47 QQ: 'SELECT 1' 2019-02-10 03:52:47 II: Finished in 0s 2019-02-10 03:53:31 Statistic: 2019-02-10 03:53:31 v6033 2019-02-10 03:53:31 q0.5 30 2019-02-10 03:53:31 SE: 2019-02-10 03:53:31 v6033 2019-02-10 03:53:31 q0.5 0.25 2019-02-10 03:53:31 2019-02-10 03:53:31 > svyby(~v6033, ~state_name, censo_design, svyquantile, 2019-02-10 03:53:31 + 0.5, ci = TRUE, keep.var = TRUE) 2019-02-10 03:53:31 QQ: 'SELECT 1' 2019-02-10 03:53:31 II: Finished in 0s 2019-02-10 03:53:31 QQ: 'select v6033 from c10' 2019-02-10 03:53:31 II: Finished in 0s 2019-02-10 03:53:31 QQ: 'SELECT 1' 2019-02-10 03:53:31 II: Finished in 0s 2019-02-10 03:53:31 QQ: 'select v0001 from c10' 2019-02-10 03:53:31 II: Finished in 0.19s 2019-02-10 03:57:31 state_name V1 se 2019-02-10 03:57:31 Rondonia Rondonia 27 0.25 2019-02-10 03:57:31 Acre Acre 24 0.25 2019-02-10 03:57:31 Amazonas Amazonas 24 0.25 2019-02-10 03:57:31 Roraima Roraima 24 0.25 2019-02-10 03:57:31 Para Para 25 0.25 2019-02-10 03:57:31 Amapa Amapa 23 0.25 2019-02-10 03:57:31 Tocantins Tocantins 26 0.25 2019-02-10 03:57:31 Maranhao Maranhao 25 0.25 2019-02-10 03:57:31 Piaui Piaui 28 0.25 2019-02-10 03:57:31 Ceara Ceara 28 0.25 2019-02-10 03:57:31 Rio Grande do Norte Rio Grande do Norte 29 0.25 2019-02-10 03:57:31 Paraiba Paraiba 29 0.25 2019-02-10 03:57:31 Pernambuco Pernambuco 29 0.25 2019-02-10 03:57:31 Alagoas Alagoas 26 0.25 2019-02-10 03:57:31 Sergipe Sergipe 27 0.25 2019-02-10 03:57:31 Bahia Bahia 28 0.25 2019-02-10 03:57:31 Minas Gerais Minas Gerais 31 0.25 2019-02-10 03:57:31 Espirito Santo Espirito Santo 30 0.25 2019-02-10 03:57:31 Rio de Janeiro Rio de Janeiro 33 0.25 2019-02-10 03:57:31 Sao Paulo Sao Paulo 32 0.25 2019-02-10 03:57:31 Parana Parana 31 0.25 2019-02-10 03:57:31 Santa Catarina Santa Catarina 31 0.25 2019-02-10 03:57:31 Rio Grande do Sul Rio Grande do Sul 33 0.25 2019-02-10 03:57:31 Mato Grosso do Sul Mato Grosso do Sul 29 0.25 2019-02-10 03:57:31 Mato Grosso Mato Grosso 28 0.25 2019-02-10 03:57:31 Goias Goias 30 0.25 2019-02-10 03:57:31 Distrito Federal Distrito Federal 29 0.25 2019-02-10 03:57:31 2019-02-10 03:57:31 > svyratio(numerator = ~nmorpob1, denominator = ~nmorpob1 + 2019-02-10 03:57:31 + one, censo_design, na.rm = TRUE) 2019-02-10 03:57:31 QQ: 'SELECT 1' 2019-02-10 03:57:31 II: Finished in 0s 2019-02-10 03:57:31 QQ: 'select v6531 from c10' 2019-02-10 03:57:31 II: Finished in 0.03s 2019-02-10 03:57:32 QQ: 'SELECT 1' 2019-02-10 03:57:32 II: Finished in 0s 2019-02-10 03:57:32 QQ: 'select one, v6531 from c10' 2019-02-10 03:57:32 II: Finished in 0.03s 2019-02-10 04:01:10 QQ: 'SELECT 1' 2019-02-10 04:01:10 II: Finished in 0s 2019-02-10 04:01:59 Ratio estimator: svyratio.svyrep.design(numerator = ~nmorpob1, denominator = ~nmorpob1 + 2019-02-10 04:01:59 one, censo_design, na.rm = TRUE) 2019-02-10 04:01:59 Ratios= 2019-02-10 04:01:59 nmorpob1 one 2019-02-10 04:01:59 nmorpob1 1 0.09317731 2019-02-10 04:01:59 SEs= 2019-02-10 04:01:59 [,1] [,2] 2019-02-10 04:01:59 [1,] 0 0.0001321418 2019-02-10 04:01:59 2019-02-10 04:01:59 > sub_censo_design <- subset(censo_design, v0640 == 2019-02-10 04:01:59 + 1) 2019-02-10 04:01:59 QQ: 'SELECT 1' 2019-02-10 04:01:59 II: Finished in 0s 2019-02-10 04:01:59 QQ: 'select v0640 from c10' 2019-02-10 04:01:59 II: Finished in 0.14s 2019-02-10 04:02:59 2019-02-10 04:02:59 > svymean(~v6033, sub_censo_design) 2019-02-10 04:02:59 QQ: 'SELECT 1' 2019-02-10 04:02:59 II: Finished in 0s 2019-02-10 04:02:59 QQ: 'select v6033 from c10' 2019-02-10 04:02:59 II: Finished in 0s 2019-02-10 04:03:11 mean SE 2019-02-10 04:03:11 v6033 45.922 0.0093 2019-02-10 04:03:11 2019-02-10 04:03:11 > this_result <- svymean(~v6033, censo_design) 2019-02-10 04:03:11 QQ: 'SELECT 1' 2019-02-10 04:03:11 II: Finished in 0s 2019-02-10 04:03:11 QQ: 'select v6033 from c10' 2019-02-10 04:03:11 II: Finished in 0s 2019-02-10 04:03:42 2019-02-10 04:03:42 > coef(this_result) 2019-02-10 04:03:42 v6033 2019-02-10 04:03:42 44.53174 2019-02-10 04:03:42 2019-02-10 04:03:42 > SE(this_result) 2019-02-10 04:03:42 [1] 0.02319129 2019-02-10 04:03:42 2019-02-10 04:03:42 > confint(this_result) 2019-02-10 04:03:42 2.5 % 97.5 % 2019-02-10 04:03:42 v6033 44.48629 44.5772 2019-02-10 04:03:42 2019-02-10 04:03:42 > cv(this_result) 2019-02-10 04:03:42 v6033 2019-02-10 04:03:42 0.0005207811 2019-02-10 04:03:42 2019-02-10 04:03:42 > grouped_result <- svyby(~v6033, ~state_name, censo_design, 2019-02-10 04:03:42 + svymean) 2019-02-10 04:03:42 QQ: 'SELECT 1' 2019-02-10 04:03:42 II: Finished in 0s 2019-02-10 04:03:42 QQ: 'select v6033 from c10' 2019-02-10 04:03:42 II: Finished in 0s 2019-02-10 04:03:42 QQ: 'SELECT 1' 2019-02-10 04:03:42 II: Finished in 0s 2019-02-10 04:03:42 QQ: 'select v0001 from c10' 2019-02-10 04:03:42 II: Finished in 0.19s 2019-02-10 04:07:15 2019-02-10 04:07:15 > coef(grouped_result) 2019-02-10 04:07:15 Rondonia Acre Amazonas Roraima 2019-02-10 04:07:15 43.47609 44.14539 44.89294 44.61115 2019-02-10 04:07:15 Para Amapa Tocantins Maranhao 2019-02-10 04:07:15 44.06793 44.36371 44.08827 44.39162 2019-02-10 04:07:15 Piaui Ceara Rio Grande do Norte Paraiba 2019-02-10 04:07:15 44.23805 43.97193 44.05621 45.40817 2019-02-10 04:07:15 Pernambuco Alagoas Sergipe Bahia 2019-02-10 04:07:15 44.35515 44.39060 43.67018 44.00062 2019-02-10 04:07:15 Minas Gerais Espirito Santo Rio de Janeiro Sao Paulo 2019-02-10 04:07:15 44.22639 44.43069 45.11529 44.86147 2019-02-10 04:07:15 Parana Santa Catarina Rio Grande do Sul Mato Grosso do Sul 2019-02-10 04:07:15 44.88411 44.42404 45.18820 45.08575 2019-02-10 04:07:15 Mato Grosso Goias Distrito Federal 2019-02-10 04:07:15 43.70309 44.16120 43.61118 2019-02-10 04:07:15 2019-02-10 04:07:15 > SE(grouped_result) 2019-02-10 04:07:15 [1] 0.25259651 0.34838929 0.25082099 0.54022560 0.14907603 0.48361606 2019-02-10 04:07:15 [7] 0.25247971 0.14310705 0.23085797 0.11920061 0.17674503 0.17917689 2019-02-10 04:07:15 [13] 0.10696337 0.24325208 0.22993718 0.10093140 0.08020715 0.14881886 2019-02-10 04:07:15 [19] 0.10910060 0.05927714 0.10775573 0.12003968 0.09892450 0.23417139 2019-02-10 04:07:15 [25] 0.23512605 0.16123461 0.34381452 2019-02-10 04:07:15 2019-02-10 04:07:15 > confint(grouped_result) 2019-02-10 04:07:15 2.5 % 97.5 % 2019-02-10 04:07:15 Rondonia 42.98101 43.97117 2019-02-10 04:07:15 Acre 43.46256 44.82822 2019-02-10 04:07:15 Amazonas 44.40134 45.38454 2019-02-10 04:07:15 Roraima 43.55233 45.66997 2019-02-10 04:07:15 Para 43.77574 44.36011 2019-02-10 04:07:15 Amapa 43.41584 45.31158 2019-02-10 04:07:15 Tocantins 43.59342 44.58313 2019-02-10 04:07:15 Maranhao 44.11114 44.67211 2019-02-10 04:07:15 Piaui 43.78558 44.69053 2019-02-10 04:07:15 Ceara 43.73830 44.20556 2019-02-10 04:07:15 Rio Grande do Norte 43.70979 44.40262 2019-02-10 04:07:15 Paraiba 45.05699 45.75935 2019-02-10 04:07:15 Pernambuco 44.14551 44.56479 2019-02-10 04:07:15 Alagoas 43.91383 44.86736 2019-02-10 04:07:15 Sergipe 43.21951 44.12085 2019-02-10 04:07:15 Bahia 43.80280 44.19844 2019-02-10 04:07:15 Minas Gerais 44.06919 44.38360 2019-02-10 04:07:15 Espirito Santo 44.13901 44.72237 2019-02-10 04:07:15 Rio de Janeiro 44.90146 45.32912 2019-02-10 04:07:15 Sao Paulo 44.74528 44.97765 2019-02-10 04:07:15 Parana 44.67292 45.09531 2019-02-10 04:07:15 Santa Catarina 44.18877 44.65931 2019-02-10 04:07:15 Rio Grande do Sul 44.99431 45.38208 2019-02-10 04:07:15 Mato Grosso do Sul 44.62678 45.54471 2019-02-10 04:07:15 Mato Grosso 43.24225 44.16393 2019-02-10 04:07:15 Goias 43.84519 44.47722 2019-02-10 04:07:15 Distrito Federal 42.93732 44.28505 2019-02-10 04:07:15 2019-02-10 04:07:15 > cv(grouped_result) 2019-02-10 04:07:15 Rondonia Acre Amazonas Roraima 2019-02-10 04:07:15 0.005810009 0.007891861 0.005587093 0.012109654 2019-02-10 04:07:15 Para Amapa Tocantins Maranhao 2019-02-10 04:07:15 0.003382869 0.010901163 0.005726686 0.003223740 2019-02-10 04:07:15 Piaui Ceara Rio Grande do Norte Paraiba 2019-02-10 04:07:15 0.005218538 0.002710834 0.004011808 0.003945917 2019-02-10 04:07:15 Pernambuco Alagoas Sergipe Bahia 2019-02-10 04:07:15 0.002411521 0.005479811 0.005265314 0.002293863 2019-02-10 04:07:15 Minas Gerais Espirito Santo Rio de Janeiro Sao Paulo 2019-02-10 04:07:15 0.001813558 0.003349461 0.002418262 0.001321338 2019-02-10 04:07:15 Parana Santa Catarina Rio Grande do Sul Mato Grosso do Sul 2019-02-10 04:07:15 0.002400754 0.002702133 0.002189167 0.005193912 2019-02-10 04:07:15 Mato Grosso Goias Distrito Federal 2019-02-10 04:07:15 0.005380078 0.003651047 0.007883632 2019-02-10 04:07:15 2019-02-10 04:07:15 > degf(censo_design) 2019-02-10 04:07:15 [1] 79 2019-02-10 04:07:15 2019-02-10 04:07:15 > svyvar(~v6033, censo_design) 2019-02-10 04:07:15 QQ: 'SELECT 1' 2019-02-10 04:07:15 II: Finished in 0s 2019-02-10 04:07:15 QQ: 'select v6033 from c10' 2019-02-10 04:07:15 II: Finished in 0s 2019-02-10 04:08:36 variance SE 2019-02-10 04:08:36 v6033 11161 19.982 2019-02-10 04:08:36 2019-02-10 04:08:36 > svymean(~v6033, censo_design, deff = TRUE) 2019-02-10 04:08:36 QQ: 'SELECT 1' 2019-02-10 04:08:36 II: Finished in 0s 2019-02-10 04:08:36 QQ: 'select v6033 from c10' 2019-02-10 04:08:36 II: Finished in 0s 2019-02-10 04:08:57 QQ: 'SELECT 1' 2019-02-10 04:08:57 II: Finished in 0s 2019-02-10 04:08:58 mean SE DEff 2019-02-10 04:08:58 v6033 44.531742 0.023191 1.115 2019-02-10 04:08:58 2019-02-10 04:08:58 > svymean(~v6033, censo_design, deff = "replace") 2019-02-10 04:08:58 QQ: 'SELECT 1' 2019-02-10 04:08:58 II: Finished in 0s 2019-02-10 04:08:58 QQ: 'select v6033 from c10' 2019-02-10 04:08:58 II: Finished in 0s 2019-02-10 04:09:20 QQ: 'SELECT 1' 2019-02-10 04:09:20 II: Finished in 0s 2019-02-10 04:09:20 mean SE DEff 2019-02-10 04:09:20 v6033 44.531742 0.023191 0.9944 2019-02-10 04:09:20 2019-02-10 04:09:20 > svyciprop(~nmorpob6, censo_design, method = "likelihood", 2019-02-10 04:09:20 + na.rm = TRUE) 2019-02-10 04:09:39 QQ: 'SELECT 1' 2019-02-10 04:09:39 II: Finished in 0s 2019-02-10 04:09:39 QQ: 'select v6531 from c10' 2019-02-10 04:09:39 II: Finished in 0.05s 2019-02-10 04:36:26 QQ: 'SELECT 1' 2019-02-10 04:36:26 II: Finished in 0s 2019-02-10 04:36:26 QQ: 'select v6531 from c10' 2019-02-10 04:36:26 II: Finished in 0.08s 2019-02-10 04:40:11 2.5% 97.5% 2019-02-10 04:40:11 nmorpob6 0.365 NA NA 2019-02-10 04:40:11 2019-02-10 04:40:11 > svyttest(v6033 ~ nmorpob6, censo_design) 2019-02-10 04:40:31 QQ: 'SELECT 1' 2019-02-10 04:40:31 II: Finished in 0s 2019-02-10 04:40:31 QQ: 'select v6033, v6531 from c10' 2019-02-10 04:40:31 II: Finished in 0.05s 2019-02-10 05:00:27 2019-02-10 05:00:27 Design-based t-test 2019-02-10 05:00:27 2019-02-10 05:00:27 data: v6033 ~ nmorpob6 2019-02-10 05:00:27 t = 10.135, df = 78, p-value = 6.936e-16 2019-02-10 05:00:27 alternative hypothesis: true difference in mean is not equal to 0 2019-02-10 05:00:27 95 percent confidence interval: 2019-02-10 05:00:27 0.4638266 0.6862225 2019-02-10 05:00:27 sample estimates: 2019-02-10 05:00:27 difference in mean 2019-02-10 05:00:27 0.5750246 2019-02-10 05:00:27 2019-02-10 05:00:27 2019-02-10 05:00:27 > svychisq(~nmorpob6 + sexo, censo_design) 2019-02-10 05:00:27 QQ: 'SELECT 1' 2019-02-10 05:00:27 II: Finished in 0s 2019-02-10 05:00:27 QQ: 'select v6531, v0601 from c10' 2019-02-10 05:00:27 II: Finished in 0.21s 2019-02-10 05:00:44 QQ: 'SELECT 1' 2019-02-10 05:00:44 II: Finished in 0s 2019-02-10 05:00:44 QQ: 'select v6531, v0601 from c10' 2019-02-10 05:00:44 II: Finished in 0.21s 2019-02-10 05:01:03 QQ: 'SELECT 1' 2019-02-10 05:01:03 II: Finished in 0s 2019-02-10 05:05:23 QQ: 'SELECT 1' 2019-02-10 05:05:23 II: Finished in 0s 2019-02-10 05:05:23 QQ: 'select v6531, v0601 from c10' 2019-02-10 05:05:23 II: Finished in 0.21s 2019-02-10 05:05:42 2019-02-10 05:05:42 Pearson's X^2: Rao & Scott adjustment 2019-02-10 05:05:42 2019-02-10 05:05:42 data: NextMethod("svychisq", design) 2019-02-10 05:05:42 F = 185.53, ndf = 1, ddf = 79, p-value < 2.2e-16 2019-02-10 05:05:42 2019-02-10 05:05:42 2019-02-10 05:05:42 > glm_result <- svyglm(v6033 ~ nmorpob6 + sexo, censo_design) 2019-02-10 05:06:01 QQ: 'SELECT 1' 2019-02-10 05:06:01 II: Finished in 0s 2019-02-10 05:06:01 QQ: 'select v6033, v6531, v0601 from c10' 2019-02-10 05:06:01 II: Finished in 0.22s 2019-02-10 05:29:30 2019-02-10 05:29:30 > summary(glm_result) 2019-02-10 05:29:34 2019-02-10 05:29:34 Call: 2019-02-10 05:29:34 NextMethod(formula = "svyglm", design) 2019-02-10 05:29:34 2019-02-10 05:29:34 Survey design: 2019-02-10 05:29:34 survey::svrepdesign(weight = as.formula(paste0("~", unique_designs[i, 2019-02-10 05:29:34 "type"], "_wgt")), repweights = bootw$repweights, type = "bootstrap", 2019-02-10 05:29:34 combined.weights = FALSE, scale = bootw$scale, rscales = bootw$rscales, 2019-02-10 05:29:34 data = paste0("c", substr(unique_designs[i, "year"], 3, 4), 2019-02-10 05:29:34 ifelse(unique_designs[i, "type"] == "pes", "", paste0("_", 2019-02-10 05:29:34 unique_designs[i, "type"]))), dbtype = "MonetDBLite", 2019-02-10 05:29:34 dbname = unique_designs[i, "dbfolder"]) 2019-02-10 05:29:34 2019-02-10 05:29:34 Coefficients: 2019-02-10 05:29:34 Estimate Std. Error t value Pr(>|t|) 2019-02-10 05:29:34 (Intercept) 44.06560 0.04385 1005.009 < 2e-16 *** 2019-02-10 05:29:34 nmorpob6 0.57361 0.05670 10.116 8.67e-16 *** 2019-02-10 05:29:34 sexofeminino 0.51847 0.05554 9.335 2.72e-14 *** 2019-02-10 05:29:34 --- 2019-02-10 05:29:34 Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 2019-02-10 05:29:34 2019-02-10 05:29:34 (Dispersion parameter for gaussian family taken to be 230099349638) 2019-02-10 05:29:34 2019-02-10 05:29:34 Number of Fisher Scoring iterations: 2 2019-02-10 05:29:34 2019-02-10 05:29:34 2019-02-10 05:29:34 > library(convey) 2019-02-10 05:29:34 2019-02-10 05:29:34 > censo_design <- convey_prep(censo_design) 2019-02-10 05:29:34 2019-02-10 05:29:34 > sub_censo_design <- subset(censo_design, v6531 >= 2019-02-10 05:29:34 + 0) 2019-02-10 05:29:34 QQ: 'SELECT 1' 2019-02-10 05:29:34 II: Finished in 0s 2019-02-10 05:29:34 QQ: 'select v6531 from c10' 2019-02-10 05:29:34 II: Finished in 0.08s 2019-02-10 05:32:57 2019-02-10 05:32:57 > svygini(~v6531, sub_censo_design, na.rm = TRUE) 2019-02-10 05:32:57 QQ: 'SELECT 1' 2019-02-10 05:32:57 II: Finished in 0s 2019-02-10 05:32:57 QQ: 'select v6531 from c10' 2019-02-10 05:32:58 II: Finished in 0.08s 2019-02-10 05:32:58 QQ: 'SELECT 1' 2019-02-10 05:32:58 II: Finished in 0s 2019-02-10 05:32:58 QQ: 'select v6531 from c10' 2019-02-10 05:32:58 II: Finished in 0.05s 2019-02-10 05:42:14 gini SE 2019-02-10 05:42:14 v6531 0.61061 6e-04 2019-02-10 05:42:14 2019-02-10 05:42:14 > close(censo_design, shutdown = TRUE) 2019-02-10 05:42:18 > test return code=0