R Graphical Manual

Browse All

Last data update: 2014.03.03

R: Compute (relative) bias summary statistic

bias	R Documentation

Compute (relative) bias summary statistic

Description

Computes the (relative) bias of a sample estimate from the parameter value. Accepts estimate and parameter values, as well as estimate values which are in deviation form. If relative bias is requested the estimate and parameter inputs are both required.

Usage

bias(estimate, parameter = NULL, relative = FALSE)

Arguments

`estimate`	a `numeric` vector or `matrix`/`data.frame` of parameter estimates. If a vector, the length is equal to the number of replications. If a `matrix`/`data.frame`, the number of rows must equal the number of replications
`parameter`	a `numeric` scalar/vector indicating the fixed parameters. If a single value is supplied and `estimate` is a `matrix`/`data.frame` then the value will be recycled for each column. If `NULL` then it will be assumed that the `estimate` input is in a deviation form (therefore `mean(estimate))` will be returned)
`relative`	logical; compute the relative bias statistic (i.e., divide the bias by the value in `parameter`)? Default is `FALSE`

Value

returns a numeric vector indicating the overall (relative) bias in the estimates

Examples


pop <- 2
samp <- rnorm(100, 2, sd = 0.5)
bias(samp, pop)
bias(samp, pop, relative = TRUE)

dev <- samp - pop
bias(dev)

# equivalent here
bias(mean(samp), pop)

# matrix input
mat <- cbind(M1=rnorm(100, 2, sd = 0.5), M2 = rnorm(100, 2, sd = 1))
bias(mat, parameter = 2)

# same, but with data.frame
df <- data.frame(M1=rnorm(100, 2, sd = 0.5), M2 = rnorm(100, 2, sd = 1))
bias(df, parameter = c(2,2))

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(SimDesign)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/SimDesign/bias.Rd_%03d_medium.png", width=480, height=480)
> ### Name: bias
> ### Title: Compute (relative) bias summary statistic
> ### Aliases: bias
> 
> ### ** Examples
> 
> 
> pop <- 2
> samp <- rnorm(100, 2, sd = 0.5)
> bias(samp, pop)
[1] -0.01781103
> bias(samp, pop, relative = TRUE)
[1] -0.008905515
> 
> dev <- samp - pop
> bias(dev)
[1] -0.01781103
> 
> # equivalent here
> bias(mean(samp), pop)
[1] -0.01781103
> 
> # matrix input
> mat <- cbind(M1=rnorm(100, 2, sd = 0.5), M2 = rnorm(100, 2, sd = 1))
> bias(mat, parameter = 2)
        M1         M2 
0.11549677 0.07795448 
> 
> # same, but with data.frame
> df <- data.frame(M1=rnorm(100, 2, sd = 0.5), M2 = rnorm(100, 2, sd = 1))
> bias(df, parameter = c(2,2))
         M1          M2 
-0.05818709  0.05027303 
> 
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>