coefplot.spls: Plot estimated coefficients of the SPLS object In spls: Sparse Partial Least Squares (SPLS) Regression and Classification

Description

Plot estimated coefficients of the selected predictors in the SPLS object.

Usage

 1 2 coefplot.spls( object, nwin=c(2,2), xvar=c(1:length(object\$A)), ylimit=NA )

Arguments

 object A fitted SPLS object. nwin Vector of the number of rows and columns in a plotting area. Default is two rows and two columns, i.e., four plots. xvar Index of variables to be plotted among the set of the selected predictors. Default is to plot the coefficients of all the selected predictors. ylimit Range of the y axis (the coefficients) in the plot. If ylimit is not specified, the y axis of the plot has the range between the minimum and the maximum of all coefficient estimates.

Details

This plot is useful for visualizing coefficient estimates of a variable for different responses. Hence, the function is applicable only with multivariate response SPLS.

NULL.

Author(s)

Dongjun Chung, Hyonho Chun, and Sunduz Keles.

References

Chun H and Keles S (2010), "Sparse partial least squares for simultaneous dimension reduction and variable selection", Journal of the Royal Statistical Society - Series B, Vol. 72, pp. 3–25.

ci.spls, and correct.spls and plot.spls.

Examples

 1 2 3 4 5 6 data(yeast) # SPLS with eta=0.7 & 8 hidden components f <- spls( yeast\$x, yeast\$y, K=8, eta=0.7 ) # Draw estimated coefficient plot of the first four variables # among the selected predictors coefplot.spls( f, xvar=c(1:4), nwin=c(2,2) )

Example output Sparse Partial Least Squares (SPLS) Regression and
Classification (version 2.2-3)

spls documentation built on May 6, 2019, 1:09 a.m.