continuum {JICO}

The continuum regression (CR) algorithm

Description

This function performs an iteration update of the JICO algorithm using the CR algorithm. Details can be found in Appendix B in the JICO paper: Wang, P., Wang, H., Li, Q., Shen, D., & Liu, Y. (2022).

Usage

continuum(
  X,
  Y,
  lambda,
  gam,
  om,
  U_old = matrix(, nrow = nrow(X), ncol = 0),
  D_old = matrix(, nrow = 0, ncol = 0),
  V_old = matrix(, nrow = 0, ncol = 0),
  Z_old = matrix(, nrow = 0, ncol = 0),
  verbose = FALSE
)

Arguments

X

The input feature matrix

Y

The input response vector

lambda

Deprecated. Regularization parameter if L2 penalization is used for CR. JICO uses zero as default.

gam

The gamma parameter in the CR algorithm. Set gam=0 for OLS model, gam=0.5 for PLS model, gam >= 1e10 for PCR model

om

The desired number of weight vectors to obtain in the CR algorithm, i.e. the predefined rank of joint or individual component.

U_old

The given inputs U from the previous JICO iteration step

D_old

The given inputs D from the previous JICO iteration step

V_old

The given inputs V from the previous JICO iteration step

Z_old

The given inputs Z from the previous JICO iteration step

verbose

Boolean. If it's desired to print out intermediate outputs

Value

A list of CR outputs that serve as the input for the next JICO iteration