MX.control: The control function for gamlssMX

In gamlss.mx: Fitting Mixture Distributions with GAMLSS

The control function for gamlssMX

Description

The function sets controls for the gamlssMX function.

Usage

MX.control(cc = 1e-04, n.cyc = 200, trace = FALSE, 
        seed = NULL, plot = TRUE, sample = NULL, ...)

Arguments

cc	convergent criterion for the EM
n.cyc	number of cycles for EM
trace	whether to print the EM iterations
seed	a number for setting the seeds for starting values
plot	whether to plot the sequence of global deviance up to convergence
sample	how large the sample to be in the starting values
...	for extra arguments

Value

Returns a list

Author(s)

Mikis Stasinopoulos and Bob Rigby

References

Rigby, R. A. and Stasinopoulos D. M. (2005). Generalized additive models for location, scale and shape,(with discussion), Appl. Statist., 54, part 3, pp 507-554.

Rigby, R. A., Stasinopoulos, D. M., Heller, G. Z., and De Bastiani, F. (2019) Distributions for modeling location, scale, and shape: Using GAMLSS in R, Chapman and Hall/CRC. An older version can be found in https://www.gamlss.com/.

Stasinopoulos D. M. Rigby R.A. (2007) Generalized additive models for location scale and shape (GAMLSS) in R. Journal of Statistical Software, Vol. 23, Issue 7, Dec 2007, https://www.jstatsoft.org/v23/i07/.

Stasinopoulos D. M., Rigby R.A., Heller G., Voudouris V., and De Bastiani F., (2017) Flexible Regression and Smoothing: Using GAMLSS in R, Chapman and Hall/CRC.

Stasinopoulos M.D., Kneib T, Klein N, Mayr A, Heller GZ. (2024) Generalized Additive Models for Location, Scale and Shape: A Distributional Regression Approach, with Applications. Cambridge University Press.

(see also https://www.gamlss.com/).

See Also

gamlss, gamlssMX, gamlssMXfits

gamlss.mx documentation built on May 29, 2024, 10:33 a.m.