logistic_reg: Logistic Regression

In CCGill/LRpadding: Padded Logistic Regression

Description

logistic_reg function that performs logistic regression, implemented here for baseline unit testing. This is almost identical to RcppNumerical::fastLR.

Usage

logistic_reg(
  x,
  y,
  start = rep(0, ncol(x)),
  eps_f = 1e-08,
  eps_g = 1e-05,
  maxit = 300
)

Arguments

x	the design matrix, with predictors as columns.
y	the response vector.
start	The initial guess of the coefficient vector.
eps_f	Iteration stops if |f-f'|/|f|<eps_f, where f and f' are the current and previous value of the objective function (negative log likelihood) respectively.
eps_g	Iteration stops if ||g|| < eps_g * max(1, ||beta||), where beta is the current coefficient vector and g is the gradient.
maxit	Maximum number of iterations.

Value

a list with the following components:

coefficients	Coefficient vector
fitted.values	The fitted probability values
linear.predictors	The fitted values of the linear part, i.e., X * beta_hat
loglikelihood	The maximized log likelihood
converged	Whether the optimization algorithm has converged

CCGill/LRpadding documentation built on May 11, 2020, 12:21 a.m.