RSSampling (version 1.0)

varRSS: Variance estimation based on ranked set sampling

Description

The varRSS function estimates the variance based on ranked set sampling as types of Stokes or Montip&Sukuman.

Usage

varRSS(X,m,r,type)

Arguments

X

An obtained ranked set sample

m

Size of units in each set

r

Number of cycles

type

character string, one of "Stokes" or "Montip".

Value

var

the estimated population variance based on ranked set sampling

Details

An obtained ranked set sample X must be m by r matrix. Stokes (1980) showed that estimator for variance is biased. Montip and Sukuman(2003) showed that for one cycle there is no unbiased estimator for variance but for more than one cycle they proposed unbiased estimator for variance.

References

Al-Hadhrami, S.A. (2010). "Estimation of the Population Variance Using Ranked Set Sampling with Auxiliary Variable". Int. J. Contemp. Math. Sciences, Vol. 5, no. 52, 2567 - 2576.

Stokes, S.L. (1980). "Estimation of Variance Using Judgment Ordered Ranked Set Samples". Biometrics, Vol. 36, No. 1, pp. 35-42.

Examples

# NOT RUN {
 data=rnorm(10000,2,1)
 samplerss=rss(data,m=4,r=3,sets=FALSE)
 ## Estimation of variance based on ranked set sample by Stokes
 varRSS(samplerss,m=4,r=3,type="Stokes")
  ## Estimation of variance based on ranked set sample by Montip&Sukuman
 varRSS(samplerss,m=4,r=3,type="Montip")

# }