rss.ELR.test {generalRSS}R Documentation

RSS empirical likelihood ratio (ELR) test for one-sample population mean

Description

The rss.ELR.test function conducts a one-sample empirical likelihood ratio test on ranked set sample data to assess the population mean.

Usage

rss.ELR.test(data, alpha = 0.05, mu0)

Arguments

data

A numeric data frame of ranked set samples with columns rank for ranks and y for data values.

alpha

A numeric value specifying the confidence level for the interval.

mu0

A numeric value indicating the hypothesized value of the mean.

Details

This function performs a one-sample empirical likelihood ratio (ELR) test on ranked set sample data using the method introduced by Ahn et al. (2024). Given a data frame of RSS data data with rank and y columns, the function calculates the empirical likelihood ratio test statistic, confidence interval, and p-value based on the hypothesized mean value mu0.

Value

RSS_mean

The RSS mean estimate.

CI

The confidence interval for the population mean.

-2*Log.LR

The empirical log likelihood ratio test statistic.

p.value

The p-value for the test.

References

S. Ahn, X. Wang, C. Moon, and J. Lim. (2024) New scheme of empirical likelihood method for ranked set sampling: Applications to two one sample problems. International Statistical Review.

See Also

rss.simulation: used for simulating Ranked Set Samples (RSS), which can serve as input.

rss.sampling: used for sampling Ranked Set Samples (RSS) from a population data set, providing input data.

Examples

## Unbalanced RSS with a set size 3 and different sample sizes of 6, 10, and 8 for each stratum,
## using imperfect ranking from a normal distribution with a mean of 0.
rss.data<-rss.simulation(H=3,nsamp=c(6,10,8),dist="normal", rho=0.8,delta=0)

## RSS empirical likelihood ratio test

rss.ELR.test(data=rss.data, alpha=0.05, mu0=0)



[Package generalRSS version 0.1.3 Index]