Usage
pplscv_cpp(X, Y, scale, method, mindices, pindices, minF, ncomp, newX, maxiter, tol, waplsgrid)
Arguments
X
a matrix of predictor variables.
Y
a matrix of a single response variable.
scale
a logical indicating whether the matrix of predictors (X) must be scaled.
method
the method used for regression. One of the following options: 'pls' or 'wapls1' or 'completewapls1p'.
mindices
a matrix with n rows and m columns where m is equivalent to the number of
resampling iterations. The elements of each column indicate the indices of the samples to be used for modeling at each
iteration.
pindices
a matrix with k rows and m columns where m is equivalent to the number of
resampling iterations. The elements of each column indicate the indices of the samples to be used for predicting at each
iteration.
minF
an integer indicating the number of minimum pls components (if the method = 'pls').
ncomp
an integer indicating the number of pls components.
newX
a matrix of one row corresponding to the sample to be predicted (if the method = 'wapls1').
maxiter
maximum number of iterations.
tol
limit for convergence of the algorithm in the nipals algorithm.
waplsgrid
the grid on which the search for the best combination of minimum and maximum pls factors of 'wapls1' is based on in case method = 'completewapls1p'.