plsRglm (version 0.7.6)

simul_data_UniYX: Data generating function for univariate plsR models

Description

This function generates a single univariate response value $Y$ and a vector of explanatory variables $(X_1,\ldots,X_{totdim})$ drawn from a model with a given number of latent components.

Usage

simul_data_UniYX(totdim, ncomp)

Arguments

totdim

Number of columns of the X vector (from ncomp to hardware limits)

ncomp

Number of latent components in the model (from 2 to 6)

Value

• vector
  $(Y,X_1,\ldots,X_{totdim})$

Details

This function should be combined with the replicate function to give rise to a larger dataset. The algorithm used is a R

References

T. Naes, H. Martens, Comparison of prediction methods for multicollinear data, Commun. Stat., Simul. 14 (1985) 545-576. http://dx.doi.org/10.1080/03610918508812458 Baibing Li, Julian Morris, Elaine B. Martin, Model selection for partial least squares regression, Chemometrics and Intelligent Laboratory Systems 64 (2002) 79-89. http://dx.doi.org/10.1016/S0169-7439(02)00051-5

See Also

simul_data_YX and simul_data_complete for generating multivariate data

Examples

simul_data_UniYX(20,6)                          

dimX <- 6
Astar <- 2

simul_data_UniYX(dimX,Astar)
(dataAstar2 <- t(replicate(50,simul_data_UniYX(dimX,Astar))))
library(plspm)
resAstar2 <- plsreg1(dataAstar2[,2:7],dataAstar2[,1], cv=TRUE)
resAstar2$Q2
plsR(dataAstar2[,1],dataAstar2[,2:7],5)


dimX <- 6
Astar <- 3

simul_data_UniYX(dimX,Astar)
(dataAstar3 <- t(replicate(50,simul_data_UniYX(dimX,Astar))))
resAstar3 <- plsreg1(dataAstar3[,2:7],dataAstar3[,1],cv=TRUE)
resAstar3$Q2
plsR(dataAstar3[,1],dataAstar3[,2:7],5)


dimX <- 6
Astar <- 4

simul_data_UniYX(dimX,Astar)
(dataAstar4 <- t(replicate(50,simul_data_UniYX(dimX,Astar))))
resAstar4 <- plsreg1(dataAstar4[,2:7],dataAstar4[,1],cv=TRUE)
resAstar4$Q2
plsR(dataAstar4[,1],dataAstar4[,2:7],5)

rm(list=c("dimX","Astar"))