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 |
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)