lsd.test {someMTP} | R Documentation |
Multivariate Left Spherically Distributed (LSD) linear scores test.
Description
It performs the multivariate Left Spherically Distributed linear scores test of L\"auter et al. (The Annals of Statistics, 1998) (see also details below).
Usage
lsd.test(resp, alternative = 1, null = NULL, D = NULL, data=NULL)
Arguments
resp |
The response vector of the regression model. May be
supplied as a vector or as a |
alternative |
The part of the design matrix corresponding to
the alternative hypothesis. The covariates of the null model do
not have to be supplied again here. May be given as a half
|
null |
The part of the design matrix corresponding to the null hypothesis. May be given as a design matrix or as a half |
data |
Only used when |
D |
is q x p matrix or it is a function with arguments |
Value
The function returns an object of class lsd.object
.
F |
the test statistic |
df |
the degrees of freedom of F |
p |
the associated p-value |
D |
the matrix used in the test (it provide information on the influence of columns in |
call: |
The matched call to |
Author(s)
Livio Finos
References
J. Laeuter, E. Glimm and S. Kropf (1998) Multivariate test based on Left-Spherically Distributed Linear Scores. The Annals of Statistics, Vol. 26, No. 5, 1972-1988
L. Finos (2011). A note on Left-Spherically Distributed Test with covariates, Statistics and Probabilty Letters, Volume 81, Issue 6, June 2011, Pages 639-641
Examples
set.seed(1)
#Standard multivariate LSD test for one sample case
X=matrix(rnorm(50),5,10)+2
lsd.test(resp=X,alternative=~1)
#Standard multivariate LSD test for two sample case
X2=X+matrix(c(0,0,1,1,1),5,10)*10
lsd.test(resp=X2,null=~1,alternative=c(0,0,1,1,1))
#General multivariate LSD test for linear predictor with covariates
lsd.test(resp=X2,null=cbind(rep(1,5),c(0,0,1,1,1)),alternative=1:5)