groceryheist/ml_measurement_error_public
1
0
Fork 0
Code

update plotting code

Browse Source
This commit is contained in:
Nathan TeBlunthuis 2023-02-28 16:14:34 -08:00
parent acb119418a
commit 69948cae1e
3 changed files with 6 additions and 7 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

5
simulations/plot_dv_example.R
View File

@ -6,7 +6,7 @@ library(filelock)
library(argparser) library(argparser)
parser <- arg_parser("Simulate data and fit corrected models.") parser <- arg_parser("Simulate data and fit corrected models.")
parser <- add_argument(parser, "--infile", default="example_4.feather", help="name of the file to read.") parser <- add_argument(parser, "--infile", default="robustness_3_dv.feather", help="name of the file to read.")
parser <- add_argument(parser, "--remember-file", default="remembr.RDS", help="name of the remember file.") parser <- add_argument(parser, "--remember-file", default="remembr.RDS", help="name of the remember file.")
parser <- add_argument(parser, "--name", default="", help="The name to safe the data to in the remember file.") parser <- add_argument(parser, "--name", default="", help="The name to safe the data to in the remember file.")
args <- parse_args(parser) args <- parse_args(parser)
@ -86,9 +86,6 @@ build_plot_dataset <- function(df){
change.remember.file(args$remember_file, clear=TRUE) change.remember.file(args$remember_file, clear=TRUE)
sims.df <- read_feather(args$infile) sims.df <- read_feather(args$infile)
sims.df[,Bzx:=NA]
sims.df[,y_explained_variance:=NA]
sims.df[,accuracy_imbalance_difference:=NA]
plot.df <- build_plot_dataset(sims.df) plot.df <- build_plot_dataset(sims.df)
remember(plot.df,args$name) remember(plot.df,args$name)

4
simulations/plot_example.R
View File

@ -9,7 +9,7 @@ source("summarize_estimator.R")
parser <- arg_parser("Simulate data and fit corrected models.") parser <- arg_parser("Simulate data and fit corrected models.")
parser <- add_argument(parser, "--infile", default="example_2.feather", help="name of the file to read.") parser <- add_argument(parser, "--infile", default="robustness_2.feather", help="name of the file to read.")
parser <- add_argument(parser, "--remember-file", default="remembr.RDS", help="name of the remember file.") parser <- add_argument(parser, "--remember-file", default="remembr.RDS", help="name of the remember file.")
parser <- add_argument(parser, "--name", default="", help="The name to safe the data to in the remember file.") parser <- add_argument(parser, "--name", default="", help="The name to safe the data to in the remember file.")
args <- parse_args(parser) args <- parse_args(parser)
@ -47,7 +47,7 @@ args <- parse_args(parser)
## var.est = var(.SD[[paste0('B',coefname,'y.est.',suffix)]]), ## var.est = var(.SD[[paste0('B',coefname,'y.est.',suffix)]]),
## est.upper.95 = quantile(.SD[[paste0('B',coefname,'y.est.',suffix)]],0.95,na.rm=T), ## est.upper.95 = quantile(.SD[[paste0('B',coefname,'y.est.',suffix)]],0.95,na.rm=T),
## est.lower.95 = quantile(.SD[[paste0('B',coefname,'y.est.',suffix)]],0.05,na.rm=T), ## est.lower.95 = quantile(.SD[[paste0('B',coefname,'y.est.',suffix)]],0.05,na.rm=T),
## N.sims = .N, ## N.sims = .
## p.sign.correct = mean(as.integer(sign.correct & (! zero.in.ci))), ## p.sign.correct = mean(as.integer(sign.correct & (! zero.in.ci))),
## variable=coefname, ## variable=coefname,
## method=suffix ## method=suffix

4
simulations/summarize_estimator.R
View File

@ -9,7 +9,7 @@ summarize.estimator <- function(df, suffix='naive', coefname='x'){
) )
grouping_vars <- c('N','m','B0', 'Bxy', 'Bzy', 'Bzx', 'Px', 'y_explained_variance', 'prediction_accuracy','outcome_formula','proxy_formula','truth_formula','z_bias','y_bias') grouping_vars <- c('N','m','B0', 'Bxy', 'Bzy', 'Bzx', 'Px', 'Py','y_explained_variance', 'prediction_accuracy','outcome_formula','proxy_formula','truth_formula','z_bias','y_bias')
grouping_vars <- grouping_vars[grouping_vars %in% names(df)] grouping_vars <- grouping_vars[grouping_vars %in% names(df)]
@ -37,6 +37,8 @@ summarize.estimator <- function(df, suffix='naive', coefname='x'){
est.lower.95 = quantile(.SD[[paste0('B',coefname,'y.est.',suffix)]],0.025,na.rm=T), est.lower.95 = quantile(.SD[[paste0('B',coefname,'y.est.',suffix)]],0.025,na.rm=T),
mean.ci.upper = mean(.SD[[paste0('B',coefname,'y.ci.upper.',suffix)]],na.rm=T), mean.ci.upper = mean(.SD[[paste0('B',coefname,'y.ci.upper.',suffix)]],na.rm=T),
mean.ci.lower = mean(.SD[[paste0('B',coefname,'y.ci.lower.',suffix)]],na.rm=T), mean.ci.lower = mean(.SD[[paste0('B',coefname,'y.ci.lower.',suffix)]],na.rm=T),
median.ci.upper = median(.SD[[paste0('B',coefname,'y.ci.upper.',suffix)]],na.rm=T),
median.ci.lower = median(.SD[[paste0('B',coefname,'y.ci.lower.',suffix)]],na.rm=T),
ci.upper.975 = quantile(.SD[[paste0('B',coefname,'y.ci.upper.',suffix)]],0.975,na.rm=T), ci.upper.975 = quantile(.SD[[paste0('B',coefname,'y.ci.upper.',suffix)]],0.975,na.rm=T),
ci.upper.025 = quantile(.SD[[paste0('B',coefname,'y.ci.upper.',suffix)]],0.025,na.rm=T), ci.upper.025 = quantile(.SD[[paste0('B',coefname,'y.ci.upper.',suffix)]],0.025,na.rm=T),
ci.lower.975 = quantile(.SD[[paste0('B',coefname,'y.ci.lower.',suffix)]],0.975,na.rm=T), ci.lower.975 = quantile(.SD[[paste0('B',coefname,'y.ci.lower.',suffix)]],0.975,na.rm=T),