LambdaSeq: Calculation of Penalty Parameter Sequence (Lambda Sequence)

In hheiling/glmmPen: High Dimensional Penalized Generalized Linear Mixed Models (pGLMM)

Calculation of Penalty Parameter Sequence (Lambda Sequence)

Description

Calculates the sequence of penalty parameters used in the model selection procedure. This function calls functions from package ncvreg.

Usage

LambdaSeq(
  X,
  y,
  family,
  offset = NULL,
  alpha = 1,
  lambda.min = NULL,
  nlambda = 10,
  penalty.factor = NULL
)

Arguments

X	matrix of standardized fixed effects (see std function in ncvreg documenation). X should not include intercept.
y	numeric vector of response values. If "survival" family, y are the event indicator values (0 if censored, 1 if event)
family	a description of the error distribution and link function to be used in the model. Currently, the glmmPen algorithm allows the Binomial ("binomial" or binomial()), Gaussian ("gaussian" or gaussian()), and Poisson ("poisson" or poisson()) families with canonical links only. See phmmPen for variable selection within proportional hazards mixed models for survival data.
offset	numeric vector that can be used to specify an a priori known component to be included in the linear predictor during fitting. This should be NULL or a numeric vector of length equal to the number of observations
alpha	Tuning parameter for the Mnet estimator which controls the relative contributions from the MCP/SCAD/LASSO penalty and the ridge, or L2, penalty. alpha=1 is equivalent to the MCP/SCAD/LASSO penalty, while alpha=0 is equivalent to ridge regression. However, alpha=0 is not supported; alpha may be arbitrarily small, but not exactly zero
lambda.min	numeric fraction between 0 and 1. The sequence of the lambda penalty parameters ranges from the maximum lambda where all fixed and random effects are penalized to 0 and a minimum lambda value, which equals a small fraction of the maximum lambda. The parameter lambda.min specifies this fraction. Default value is set to NULL, which automatically selects lambda.min to equal 0.01 when the number of observations is greater than the number of fixed effects predictors and 0.05 otherwise. Only used if either lambda0_seq or lambda1_seq remain unspecified by the user (one or both of these sequence arguments set to NULL) and, consequently, one or more default sequences need to be calculated.
nlambda	positive integer specifying number of penalty parameters (lambda) with which to fit a model.
penalty.factor	an optional numeric vector equal to the fixef_noPen argument in glmmPen

Value

numeric sequence of penalty parameters of length nlambda ranging from the minimum penalty parameter (first element) equal to fraction lambda.min multiplied by the maximum penalty parameter to the maximum penalty parameter (last element)

hheiling/glmmPen documentation built on Jan. 15, 2024, 11:47 p.m.