envelope_bes: envelope_bes

In vpnsctl/bbreg: Bessel and Beta Regressions via Expectation-Maximization Algorithm for Continuous Bounded Data

Description

Function to calculate envelopes based on residuals for the bessel regression.

Usage

envelope_bes(
  residual,
  kap,
  lam,
  x,
  v,
  nsim_env,
  prob,
  n,
  link.mean,
  link.precision,
  em_controls,
  optim_method,
  optim_controls
)

Arguments

residual	character indicating the type of residual ("pearson", "score" or "quantile").
kap	coefficients in kappa related to the mean parameter.
lam	coefficients in lambda related to the precision parameter.
x	matrix containing the covariates for the mean submodel. Each column is a different covariate.
v	matrix containing the covariates for the precision submodel. Each column is a different covariate.
nsim_env	number of synthetic data sets to be generated.
prob	confidence level of the envelope (number between 0 and 1).
n	sample size.
link.mean	a string containing the link function for the mean. The possible link functions for the mean are "logit","probit", "cauchit", "cloglog".
link.precision	a string containing the link function the precision parameter. The possible link functions for the precision parameter are "identity", "log", "sqrt".
em_controls	a list containing two elements: maxit that contains the maximum number of iterations of the EM algorithm; em_tol that defines the tolerance value to control the convergence criterion in the EM-algorithm.
optim_method	main optimization algorithm to be used. The available methods are the same as those of optim function.
optim_controls	a list of control arguments to be passed to the optim function in the optimization of the model. For the control options, see the 'Details' in the help of optim for the possible arguments.

Value

Matrix with dimension 2 x n (1st row = upper bound, second row = lower bound).

vpnsctl/bbreg documentation built on March 14, 2021, 12:11 a.m.