Fit IRWPLS and IRWPLSF model
Fit Iteratively ReWeighted Least Squares (IRWPLS) with an option of Firth's bias reduction procedure (IRWPLSF) for two-group classification
glpls1a(X, y, K.prov = NULL, eps = 0.001, lmax = 100, b.ini = NULL, denom.eps = 1e-20, family = "binomial", link = NULL, br = TRUE)
- n by p design matrix (with no intercept term)
- response vector 0 or 1
- number of PLS components, default is the rank of X
- tolerance for convergence
- maximum number of iteration allowed
- initial value of regression coefficients
- small quanitity to guarantee nonzero denominator in deciding convergence
- glm family,
binomialis the only relevant one here
- link function,
logitis the only one practically implemented now
- TRUE if Firth's bias reduction procedure is used
- regression coefficients
- whether convergence is achieved
- total number of iterations
- whether Firth's procedure is used
- the matrix of loadings
- Ding, B.Y. and Gentleman, R. (2003) Classification using generalized partial least squares.
- Marx, B.D (1996) Iteratively reweighted partial least squares estimation for generalized linear regression. Technometrics 38(4): 374-381.
x <- matrix(rnorm(20),ncol=2) y <- sample(0:1,10,TRUE) ## no bias reduction glpls1a(x,y,br=FALSE) ## no bias reduction and 1 PLS component glpls1a(x,y,K.prov=1,br=FALSE) ## bias reduction glpls1a(x,y,br=TRUE)
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