WH_1d_outer: Whittaker-Henderson Smoothing (Maximum Likelihood, optimize...

In WH: Enhanced Implementation of Whittaker-Henderson Smoothing

Whittaker-Henderson Smoothing (Maximum Likelihood, optimize function)

Description

Whittaker-Henderson Smoothing (Maximum Likelihood, optimize function)

Usage

WH_1d_outer(
  d,
  ec,
  y,
  wt,
  q = 2,
  p,
  criterion = "REML",
  lambda = 1000,
  reg = FALSE,
  verbose = FALSE,
  accu_crit = 1e-12,
  accu_dev = 1e-12
)

Arguments

d	Vector of observed events
ec	Vector of central exposure
y	Vector of observations
wt	Optional vector of weights
q	Order of penalization. Polynoms of degrees q - 1 are considered smooth and are therefore unpenalized
p	The number of eigenvectors to keep
criterion	Criterion used to choose the smoothing parameter. One of "GCV" (default), "AIC" or "BIC".
lambda	Initial smoothing parameter
reg	Should the regression framework be used ? Boolean. If TRUE, will stop after the first iteration.
verbose	Should information about the optimization progress be displayed
accu_crit	Tolerance for the convergence of the outer optimization procedure
accu_dev	Tolerance for the convergence of the optimization procedure

Value

An object of class "WH_1d" i.e. a list containing model fit, variance, residuals and degrees of freedom as well as diagnosis to asses the quality of the fit.

WH documentation built on Sept. 11, 2024, 9:12 p.m.