utils: Internal boxcoxmix functions

In boxcoxmix: Box-Cox-Type Transformations for Linear and Logistic Models with Random Effects

Internal boxcoxmix functions

Description

auxiliary functions are not intended to be directly called from the user.

Usage

np.boxcox(
  formula,
  groups = 1,
  data,
  K = 3,
  tol = 0.5,
  lambda = 1,
  steps = 500,
  EMdev.change = 1e-04,
  plot.opt = 1,
  verbose = TRUE,
  start = "gq",
  ...
)

vc.boxcox(
  formula,
  groups = 1,
  data,
  K = 3,
  tol = 0.5,
  lambda = 1,
  steps = 500,
  EMdev.change = 1e-04,
  plot.opt = 1,
  verbose = TRUE,
  start = "gq",
  ...
)

np.em(
  y,
  x,
  K,
  lambda = 1,
  steps = 500,
  tol = 0.5,
  start = "gq",
  EMdev.change = 1e-04,
  plot.opt = 1,
  verbose = TRUE,
  ...
)

vc.em(
  y,
  x,
  sizes = 1,
  K,
  lambda,
  steps = 500,
  tol = 0.5,
  start = "gq",
  EMdev.change = 1e-04,
  plot.opt = 1,
  verbose = TRUE,
  ...
)

np.estep(y, x, lambda, p, beta, z, sigma)

vc.estep(Y, X, sizes = 1, lambda, p, beta, z, sigma)

np.mstep(y, x, beta, lambda, w)

vc.mstep(Y, X, sizes = 1, beta, lambda, w)

np.theta(y, x, lambda, beta, z)

vc.theta(Y, X, sizes, lambda, beta, z)

np.bhat(y, x, w, z, lambda)

bhat(Y, X, sizes, w, z, lambda)

np.zk(y, x, w, beta, lambda)

zk(Y, X, sizes, w, beta, lambda)

fik(y, x, lambda, beta, z, sigma)

mik(Y, X, sizes, lambda, beta, z, sigma)

yhat(v, lambda = 1)

ytrans(y, lambda = 1)

gqz(numnodes = 20, minweight = 1e-06)

masspoint.class(object)

Arguments

formula	a formula describing the transformed response and the fixed effect model (e.g. y ~ x).
groups	the random effects. To fit overdispersion models , set groups = 1.
data	a data frame containing variables used in the fixed and random effect models.
K	the number of mass points.
tol	a positive scalar (usually, 0< tol <= 2)
lambda	a transformation parameter, setting lambda=1 means 'no transformation'.
steps	maximum number of iterations for the EM algorithm.
EMdev.change	a small scalar, with default 0.0001, used to determine when to stop EM algorithm.
plot.opt	Set plot.opt=1, to plot the disparity against iteration number. Use plot.opt=2 for tolfind.boxcox and plot.opt=3 for optim.boxcox.
verbose	If set to FALSE, no printed output on progress.
start	a description of the initial values to be used in the fitted model, Quantile-based version "quantile" or Gaussian Quadrature "gq" can be set.
...	extra arguments will be ignored.
y	..
x	..
sizes	..
p	..
beta	..
z	..
sigma	..
Y	..
X	..
w	..
v	..
numnodes	..
minweight	..
object	..

Author(s)

Amani Almohaimeed and Jochen Einbeck

boxcoxmix documentation built on Sept. 11, 2024, 8:26 p.m.