modelspec: Generate non-nested candidate models

In cvmaPLFAM: Cross-Validation Model Averaging for Partial Linear Functional Additive Models

Generate non-nested candidate models

Description

Specify non-nested candidate models, according to the prescribed number of scalar predictors and the number of functional principal components (FPCs). Each candidate model comprises at least one scalar predictor and one FPC, leading to a total number of candidate models (2^nump-1)*(2^numq-1).

Usage

modelspec(nump, numq)

Arguments

nump	The number of scalar predictors used in candidate models.
numq	The number of functional principal components (FPCs) used in candidate models.

Value

A list of

a1	The number of scalar predictors in each candidate model.
a2	The number of FPCs in each candidate model.
a3	The index for each component in each candidate model.

Examples

# Given nump = 2 and numq = 2, resulting in 9 candidate models
modelspec(2, 2)
#$a1
#[1] 2 2 2 1 1 1 1 1 1
#$a2
#[1] 2 1 1 2 1 1 2 1 1
#$a3
#      [,1] [,2] [,3] [,4]
# [1,]    1    2    3    4
# [2,]    1    2    3    0
# [3,]    1    2    0    4
# [4,]    1    0    3    4
# [5,]    1    0    3    0
# [6,]    1    0    0    4
# [7,]    0    2    3    4
# [8,]    0    2    3    0
# [9,]    0    2    0    4

cvmaPLFAM documentation built on July 9, 2023, 6:30 p.m.