74 lines
2.3 KiB
R
74 lines
2.3 KiB
R
source("RemembR/R/RemembeR.R")
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library(arrow)
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library(data.table)
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library(ggplot2)
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library(filelock)
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library(argparser)
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parser <- arg_parser("Simulate data and fit corrected models.")
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parser <- add_argument(parser, "--infile", default="", help="name of the file to read.")
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parser <- add_argument(parser, "--name", default="", help="The name to safe the data to in the remember file.")
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args <- parse_args(parser)
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source("summarize_estimator.R")
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build_plot_dataset <- function(df){
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x.true <- summarize.estimator(df, 'true','x')
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z.true <- summarize.estimator(df, 'true','z')
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x.naive <- summarize.estimator(df, 'naive','x')
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z.naive <- summarize.estimator(df, 'naive','z')
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x.loa0.feasible <- summarize.estimator(df, 'loa0.feasible','x')
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z.loa0.feasible <- summarize.estimator(df,'loa0.feasible','z')
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x.loa0.mle <- summarize.estimator(df, 'loa0.mle', 'x')
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z.loa0.mle <- summarize.estimator(df, 'loa0.mle', 'z')
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x.loco.feasible <- summarize.estimator(df, 'loco.feasible', 'x')
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z.loco.feasible <- summarize.estimator(df, 'loco.feasible', 'z')
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x.loco.mle <- summarize.estimator(df, 'loco.mle', 'x')
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z.loco.mle <- summarize.estimator(df, 'loco.mle', 'z')
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z.loco.amelia <- summarize.estimator(df, 'amelia.full', 'z')
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x.loco.amelia <- summarize.estimator(df, 'amelia.full', 'x')
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z.loco.zhang <- summarize.estimator(df, 'zhang', 'z')
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x.loco.zhang <- summarize.estimator(df, 'zhang', 'x')
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accuracy <- df[,mean(accuracy)]
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plot.df <- rbindlist(list(x.true,z.true,x.loa0.feasible,z.loa0.feasible,x.naive,z.naive,x.loa0.mle,z.loa0.mle,x.loco.feasible, z.loco.feasible, z.loco.mle, x.loco.mle, x.loco.amelia, z.loco.amelia, z.loco.zhang, x.loco.zhang),use.names=T)
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plot.df[,accuracy := accuracy]
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plot.df <- plot.df[,":="(sd.est=sqrt(var.est)/N.sims)]
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return(plot.df)
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}
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plot.df <- read_feather(args$infile)
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print(unique(plot.df$N))
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# df <- df[apply(df,1,function(x) !any(is.na(x)))]
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if(!('Bzx' %in% names(plot.df)))
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plot.df[,Bzx:=NA]
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if(!('accuracy_imbalance_difference' %in% names(plot.df)))
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plot.df[,accuracy_imbalance_difference:=NA]
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unique(plot.df[,'accuracy_imbalance_difference'])
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#plot.df <- build_plot_dataset(df[accuracy_imbalance_difference==0.1][N==700])
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plot.df <- build_plot_dataset(plot.df)
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change.remember.file("remember_irr.RDS",clear=TRUE)
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remember(plot.df,args$name)
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