MNM (version 0.95-2)

mv.2sample.est: Multivariate Two Sample Shift Estimates

Description

Estimates the multivariate shift for different score functions and their asymptotic covariance matrices in the two sample case.

Usage

mv.2sample.est(X, g, score = "identity", stand = "outer", 
               maxiter = 100, eps = 1e-06, na.action = na.fail,
               ...)

Arguments

X

a numeric data frame or matrix.

g

a factor with two levels

score

the score to be used. Possible choices are identity, sign and rank.

stand

the standardization method used. Possible choices are outer and inner.

maxiter

maximum number of iterations. Used only for score = "sign" and score = "rank".

eps

convergence tolerance. Used only for score = "sign" and score = "rank".

na.action

a function which indicates what should happen when the data contain 'NA's. Default is to fail.

...

arguments that can be passed on to functions used for the estimation of location.

Value

• A list with class 'mvloc' containing the following components:
• location
  the location estimate as a vector.
• vcov
  the asymptotic covariance matrix of the location estimate.
• est.name
  name of the location estimate.
• dname
  name of data set for which the location was computed.

Details

This implements the location estimates and their asymptotic covariance matrices as described in chapter 11 of the MNM book. Note that the shift is the parameter for the defference between 'values of level 1 - values of level 2' where the levels are as defined in the factor g. For the general c sample location case the function mv.l1lm might be used.

References

Oja, H. (2010), Multivariate Nonparametric Methods with R, Springer.

See Also

spatial.sign, spatial.signrank

Examples

X1<- rmvnorm(50,c(0,0,0))
X2<- rmvnorm(70,c(1,1,2))
X<-rbind(X1,X2)
g<-factor(rep(1:2,c(50,70)))

  est.Hot.X <- mv.2sample.est(X, g)
  est.SS.o.X <- mv.2sample.est(X, g, "s")
  est.SS.i.X <- mv.2sample.est(X, g, "s", "i")
  est.SR.o.X <- mv.2sample.est(X, g, "r")
  est.SR.i.X <- mv.2sample.est(X, g, "r", "i")

  est.SS.o.X
  
  summary(est.SS.o.X)
  
  # plotting
   
  plotMvloc(est.Hot.X, est.SS.i.X, est.SR.i.X)