find_w12bic: Internal mixedCCA function finding w1 and w2 given R1, R2 and...

Description Usage Arguments Value References

View source: R/KendallCCA.R

Description

Internal mixedCCA function finding w1 and w2 given R1, R2 and R12

Usage

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find_w12bic(
  n,
  R1,
  R2,
  R12,
  lamseq1,
  lamseq2,
  w1init,
  w2init,
  BICtype,
  maxiter = 100,
  tol = 0.01,
  trace = FALSE,
  lassoverbose = FALSE
)

Arguments

n

Sample size

R1

Correlation matrix of dataset X1 (p1 by p1)

R2

Correlation matrix of dataset X2 (p2 by p2)

R12

Correlation matrix between the dataset X1 and the dataset X2 (p1 by p2)

lamseq1

A sequence of lambda values for the datasets X1. It can be a scalar (a vector of one value). should be the same length with lamseq2.

lamseq2

A sequence of lambda values for the datasets X2. It can be a scalar (a vector of one value). should be the same length with lamseq1.

w1init

An initial vector of length p1 for canonical direction w1.

w2init

An initial vector of length p1 for canonical direction w2.

BICtype

Either 1 or 2: For more details for two options, see the reference.

maxiter

The maximum number of iterations allowed.

tol

The desired accuracy (convergence tolerance).

trace

If trace = TRUE, progress per each iteration will be printed. The default value is FALSE.

lassoverbose

If lassoverbose = TRUE, all warnings from lassobic optimization regarding convergence will be printed. The default value is lassoverbose = FALSE.

Value

find_w12bic returns a data.frame containing

References

Yoon G., Carroll R.J. and Gaynanova I. (2020) "Sparse semiparametric canonical correlation analysis for data of mixed types" <doi:10.1093/biomet/asaa007>.


mixedCCA documentation built on March 21, 2021, 1:07 a.m.