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$X, outcome_col = admix$y)
fit <- plmm(design = admix_design)
summary(fit, idx = 97)
#> lasso-penalized regression model with n=197, p=101 at lambda=0.00052
#> -------------------------------------------------
#> The model converged 
#> -------------------------------------------------
#> # of non-zero coefficients:  98 
#> -------------------------------------------------