get_interaction_patterns

Generates all possible interaction patterns for 2 or 3 variables. This is
used in part for identifying which interactions and expansions to exclude
(provided to "exclude_these_expansions" argument of lgspline) based on
formulas provided.

internal

Implements Lagrangian multiplier smoothing splines for flexible
nonparametric regression and function estimation. Provides tools for fitting,
prediction, and inference using a constrained optimization approach to
enforce smoothness.
Supports generalized linear models, Weibull accelerated failure time (AFT) models,
quadratic programming problems, and customizable arbitrary correlation structures.
Options for fitting in parallel are provided. The method builds upon the framework described
by Ezhov et al. (2018) <doi:10.1515/jag-2017-0029> using Lagrangian multipliers
to fit cubic splines. For more information on correlation structure estimation,
see Searle et al. (2009) <ISBN:978-0470009598>. For quadratic programming and
constrained optimization in general, see Nocedal & Wright (2006) <doi:10.1007/978-0-387-40065-5>.
For a comprehensive background on smoothing splines, see Wahba (1990)
<doi:10.1137/1.9781611970128> and Wood (2006) <ISBN:978-1584884743>
"Generalized Additive Models: An Introduction with R".

Matthew Davis

lgspline

Lagrangian Multiplier Smoothing Splines for Smooth Function
Estimation

get_interaction_patterns function

<dl><dt>vars</dt>
<dd>Character vector of variable names</dd></dl>

Arguments

Generate Interaction Variable Patterns — get_interaction_patterns

<dl>

<dt>vars</dt>
<dd>Character vector of variable names</dd>

</dl>

get_interaction_patterns: Generate Interaction Variable Patterns

Description

Usage

Value

Arguments