All Scores

Description

An object of class scores which includes the score function and it's derivative for rank-based regression inference.

Usage

data(wscores)

Format

The format is: Formal class 'scores' [package ".GlobalEnv"] with 2 slots ..@ phi :function (u) ..@ Dphi:function (u)

Details

Using Wilcoxon (linear) scores leads to inference which has ARE of 0.955 to least squares (ML) when the data are normal. Wilcoxon scores are optimal when the underlying error distribution is logistic. Normal scores are optimal when the data are normally distributed. Log-rank scores are optimal when the data are from an exponential distribution, e.g. in a proportional hazards model. Log-Generalized F scores can also be used in the analysis of survival data (see Hettmansperger and McKean p. 233).

References

Hettmansperger, T.P. and McKean J.W. (2011), Robust Nonparametric Statistical Methods, 2nd ed., New York: Chapman-Hall.

Examples

data(wscores)
x<-runif(10)
y<-rlogis(10)
rfit(y~x,scores=wscores)

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(Rfit)
Loading required package: quantreg
Loading required package: SparseM

Attaching package: 'SparseM'

The following object is masked from 'package:base':

    backsolve

> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/Rfit/allscores.Rd_%03d_medium.png", width=480, height=480)
> ### Name: allscores
> ### Title: All Scores
> ### Aliases: wscores nscores bentscores1 bentscores2 bentscores3
> ###   bentscores4 logGFscores logrank.scores
> ### Keywords: datasets
> 
> ### ** Examples
> 
> data(wscores)
> x<-runif(10)
> y<-rlogis(10)
> rfit(y~x,scores=wscores)
Call:
rfit.default(formula = y ~ x, scores = wscores)

Coefficients:
(Intercept)           x 
   0.568654   -1.174484 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>