spls-internal {spls} | R Documentation |
Internal SPLS functions.
heatmap.spls( mat, coln=16, as='n', ... ) spls.dv( Z, eta, kappa, eps, maxstep ) ust( b, eta ) correctp( x, y, eta, K, kappa, select, fit ) cv.split( y, fold ) wpls( x, y, V, K=ncol(x), type="pls1", center.x=TRUE, scale.x=FALSE ) sgpls.binary( x, y, K, eta, scale.x=TRUE, eps=1e-5, denom.eps=1e-20, zero.eps=1e-5, maxstep=100, br=TRUE, ftype='iden' ) sgpls.multi( x, y, K, eta, scale.x=TRUE, eps=1e-5, denom.eps=1e-20, zero.eps=1e-5, maxstep=100, br=TRUE, ftype='iden' ) cv.sgpls.binary( x, y, fold=10, K, eta, scale.x=TRUE, plot.it=TRUE, br=TRUE, ftype='iden' ) cv.sgpls.multi( x, y, fold=10, K, eta, scale.x=TRUE, plot.it=TRUE, br=TRUE, ftype='iden' )
These are not to be called by the user.
Dongjun Chung, Hyonho Chun, and Sunduz Keles.
Chung, D. and Keles, S. (2009). "Sparse partial least squares classification for high dimensional data" (http://www.stat.wisc.edu/~keles/Papers/C_SPLS.pdf).
Chun, H. and Keles, S. (2009). "Sparse partial least squares for simultaneous dimension reduction and variable selection", To appear in Journal of the Royal Statistical Society - Series B (http://www.stat.wisc.edu/~keles/Papers/SPLS_Nov07.pdf).