logisticc: Logistic Regression (c++)

In MGallow/logitr: Penalized Logistic Regression

Description

Computes the coefficient estimates for logistic regression. ridge regularization and bridge regularization optional.

Usage

logisticc(X, y, lam = 0, alpha = 1.5, penalty = "none",
  intercept = TRUE, method = "IRLS", tol = 1e-05, maxit = 1e+05,
  vec = 0L, init = 0L)

Arguments

X	matrix
y	matrix or vector of response values 0,1
lam	optional tuning parameter for ridge regularization term. Defaults to 'lam = 0'
alpha	optional tuning parameter for bridge regularization term. Defaults to 'alpha = 1.5'
penalty	choose from c('none', 'ridge', 'bridge'). Defaults to 'none'
intercept	Defaults to TRUE
method	optimization algorithm. Choose from 'IRLS' or 'MM'. Defaults to 'IRLS'
tol	tolerance - used to determine algorithm convergence. Defaults to 1e-5
maxit	maximum iterations. Defaults to 1e5
vec	optional vector to specify which coefficients will be penalized
init	optional initialization for MM algorithm

Value

returns beta estimates (includes intercept), total iterations, and gradients.

MGallow/logitr documentation built on May 6, 2019, 12:06 a.m.