Calculate the estimated projection matrices for every kernels in the kernel library.
estimate_base(Y, X, K_list, mode, lambda, ...)(matrix, n*1) The vector of response variable.
(matrix, n*d_fix) The fixed effect matrix.
(list of matrices) A nested list of kernel term matrices. The first level corresponds to each base kernel function in kern_func_list, the second level corresponds to each kernel term specified in the formula.
(character) A character string indicating which tuning parameter criteria is to be used.
(numeric) A numeric string specifying the range of tuning parameter to be chosen. The lower limit of lambda must be above 0.
Additional parameters to pass to estimate_ridge.
(list of length K) A list of projection matrices for each kernel in the kernel library.
(list of length K) A list of projection matrices to kernel space for each kernel in the kernel library.
(list of length K) A list of fixed effect estimators for each kernel in the kernel library.
(list of length K) A list of kernel effect estimates for each kernel in the kernel library.
(list of length K) A list of kernel effects for each kernel in the kernel library.
(list of length K) A list of projection matrices for each kernel in the kernel library.
(list of length K) A list of selected tuning parameters for each kernel in the kernel library.
(matrix, n*K) A n\*K matrix indicating errors.
For a given mode, this function returns a list of projection matrices for every kernel in the kernel library and a n*K matrix indicating errors.
Jeremiah Zhe Liu and Brent Coull. Robust Hypothesis Test for Nonlinear Effect with Gaussian Processes. October 2017.