RSSampling (version 1.0)

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

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

Value

sets

the ranked sets where ranked set sample is chosen from

sample

the obtained ranked set sample of X

Details

Target population X must be a vector.

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

# NOT RUN {
  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")

# }