np.boxcox: 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

Amani Almohaimeed and Jochen Einbeck