summary.plmm: A summary method for the plmm objects

In plmmr: Penalized Linear Mixed Models for Correlated Data

A summary method for the plmm objects

Description

A summary method for the plmm objects

Usage

## S3 method for class 'plmm'
summary(object, lambda, idx, eps = 1e-05, ...)

Arguments

object	An object of class plmm
lambda	The regularization parameter value at which inference should be reported.
idx	Alternatively, lambda may be specified by an index; idx=10 means: report inference for the 10th value of lambda along the regularization path. If both lambda and idx are specified, lambda takes precedence.
eps	If lambda is given, eps is the tolerance for difference between the given lambda value and a lambda value from the object. Defaults to 0.0001 (1e-5)
...	Not used

Value

The return value is an object with S3 class summary.plmm. The class has its own print method and contains the following list elements:

• penalty: The penalty used by plmm (e.g. SCAD, MCP, lasso)

• n: Number of instances/observations

• std_X_n: the number of observations in the standardized data; the only time this would differ from 'n' is if data are from PLINK and the external data does not include all the same samples

• p: Number of regression coefficients (not including the intercept)

• converged: Logical indicator for whether the model converged

• lambda: The lambda value at which inference is being reported

• lambda_char: A formatted character string indicating the lambda value

• nvars: The number of nonzero coefficients (again, not including the intercept) at that value of lambda

• nonzero: The column names indicating the nonzero coefficients in the model at the specified value of lambda

Examples

admix_design <- create_design(X = admix$X, y = admix$y)
fit <- plmm(design = admix_design)
summary(fit, idx = 97)

plmmr documentation built on April 4, 2025, 12:19 a.m.