wilstep {rlme}

Wilcoxon One Step Rank-based Estimate in GR Method

Description

Gets weighted rank based fittings for nested designs.

Usage

wilstep(I, sec, mat, init = F, y, x, sigmaa2 = 1, sigmaw2 = 1,
  sigmae2 = 1, thetaold = c(0), eps = 1e-04, iflag2 = 0,
  rprpair = "hl-disp")

Arguments

I

Number of clusters.

sec

A vector of subcluster numbers in clusters.

mat

A matrix of numbers of observations in subclusters. Dimension is Ixmax(number ofsubclusters). Each row indicates one cluster.

init

boolean

y

Response vector of nx1.

x

Design matrix, pxn, without intercept.

sigmaa2

Initial sigma for cluster in three-level design.

sigmaw2

Initial sigma for subcluster in three-level design.

sigmae2

Initial sigma for error in three-level design.

thetaold

Initial input.

eps

Epsilon value

iflag2

y or n

rprpair

Either 'hl-disp' or 'med-mad'

Details

Initial inputs are from the independent model.

Author(s)

J. W. McKean and Y. K. Bilgic

References

Y. K. Bilgic and J. W. McKean. Iteratively reweighted generalized rank-based method in mixed models. 2013. Under preperation.

J. T. Terpstra and J. W. McKean. Rank-based analysis of linear models using R. Journal of Statistical Software, 14(7) 1 - 26, 7 2005. ISSN 1548-7660. URL http://www.jstatsoft.org/v14/i07.