WilcoxonSignedRank-help: Wilcoxon signed rank test with RSS

In RSSampling: Ranked Set Sampling

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")

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).

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

References

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

Examples

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)


  

RSSampling documentation built on May 2, 2019, 4:28 a.m.