RSSampling (version 1.0)

wsrtestrss: Wilcoxon signed rank test with RSS

Description

It performs the RSS version of the Wilcoxon signed rank test given by Chen et. al.(2003).

Usage

wsrtestrss(sampledata,m,r,delta0=0,alpha=0.05,alternative="two.sided")

Arguments

sampledata

An obtained ranked set sample

m

Number of units in each set (set size)

r

Number of cycles

delta0

The median value of difference in the null hypothesis

alpha

The significance level (by default = 0.05).

alternative

Character string defining the alternative hypothesis, one of "two.sided", "less" or "greater" (by default = "two.sided")

Value

median

median value of the sample

sign.rank.test.stat

The value of the Wilcoxon signed rank test statistic

z.test

the z statistic for test

p.value

the p value for the test

Details

The test statistics and an approximate confidence intervals are constructed by using the normal approximation. Also note that, we assume that the ranking mechanism in the RSS is consistent. For more details please refer to Chen et. al.(2003, pg. 124-133).

References

Chen, Z., Bai Z., Sinha B. K. (2003). Ranked Set Sampling: Theory and Application. New York: Springer.

Examples

# NOT RUN {
library("LearnBayes")
mu=c(1,1.2,2)
Sigma <- matrix(c(1,2,0,2,5,0.5,0,0.5,3), 3, 3)
x <- rmnorm(10000, mu, Sigma)
xx=as.numeric(x[,1])
xy=as.numeric(x[,2])
samplerss=con.rss(xx,xy,m=3,r=12,concomitant=TRUE)
sample.x=as.numeric(samplerss$sample.x)
sample.y=as.numeric(samplerss$sample.y)
difference=sample.x-sample.y
wsrtestrss(difference,m=3,r=12,delta0=0)


  
# }