Mrss: Selecting a ranked set sample (classical or modified)

In RSSampling: Ranked Set Sampling

Description

The Mrss function samples from a target population by using modified ranked set sampling methods.

Usage

  Mrss(X,m,r=1,type="r",sets=FALSE,p)

Arguments

X	A vector of target population
m	Size of units in each set
r	Number of cycles. (By default = 1)
sets	logical; if TRUE, ranked set samples are given with ranked sets (see rankedsets)
type	type of the modified RSS method. "r" for traditional RSS, "p" for Percentile RSS, "m" for Median RSS, "bg" for Balanced Groups RSS, "e" for Extreme RSS. (By default = "r")
p	Value of percentile for Percentile RSS method

Details

Target population X must be a vector.

Value

sets	the ranked sets where ranked set sample is chosen from
sample	the obtained ranked set sample of X

References

McIntyre, G. A. (1952). A method for unbiased selective sampling, using ranked sets. Australian Journal of Agricultural Research, 3(4), 385-390.

Samawi, H. M., Ahmed, M. S., & Abu-Dayyeh, W. (1996). Estimating the population mean using extreme ranked set sampling. Biometrical Journal, 38(5), 577-586.

Muttlak, H. A. (1997). Median ranked set sampling. Journal of Applied Statistical Sciences, 6(4), 245-255.

Muttlak, H. A. (2003). Modified ranked set sampling methods. Pakistan Journal Of Statistics, 19(3), 315-324.

Jemain, A. A., Al-Omari, A., & Ibrahim, K. (2008). Some variations of ranked set sampling. Electronic Journal of Applied Statistical Analysis, 1(1), 1-15.

See Also

con.Mrss, Rrss, Drss

Examples

  data=rgamma(10000,1,1)
  ## Selecting a median ranked set sample
  Mrss(data,m=4,r=5,sets=TRUE,type="m")
   ## Selecting an extreme ranked set sample
  Mrss(data,m=3,r=5,sets=TRUE,type="e")
   ## Selecting a percentile ranked set sample
  Mrss(data,m=4,r=3,sets=TRUE,type="p",p=0.2)
   ## Selecting a balanced groups ranked set sample
  Mrss(data,m=6,r=2,sets=TRUE,type="bg")

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