PLSR1Bin function

Partial Least Squares Regression with Binary Response

Fits Partial Least Squares Regression with Binary Response

PLSR1Bin(Y, X, S = 2, InitTransform = 5, grouping = NULL, 
tolerance = 5e-06, maxiter = 100, show = FALSE, penalization = 0, 
cte = TRUE, Algorithm = 1, OptimMethod = "CG")

Arguments

• Y: The response
• X: The matrix of independent variables
• S: The Dimension of the solution
• InitTransform: Initial transform for the X matrix
• grouping: Factor for grouping the observations
• tolerance: Tolerance for convergence of the algorithm
• maxiter: Maximum Number of iterations
• show: Show the steps of the algorithm
• penalization: Penalization for the Ridge Logistic Regression
• cte: Should a constant be included in the model?
• Algorithm: Algorithm used in the calculations
• OptimMethod: Optimization methods from optim

Details

The procedure uses the algorithm proposed by Bastien et al () to fit a Partial Lest Squares Regression when the response is Binary. The procedure will be later converted into a Biplot to visulize the results.

Returns

Still to be finished

Author(s)

Jose Luis Vicente Villardon

Examples

# No examples yet