NP.control: Control function for gamlssNP

In gamlss.mx: Fitting Mixture Distributions with GAMLSS

Control function for gamlssNP

Description

This is a control function for gamlssNP function.

Usage

NP.control(EMcc = 0.001, EMn.cyc = 200, damp = TRUE, 
           trace = TRUE, plot.opt = 3, ...)

Arguments

EMcc	convergence criterion for the EM
EMn.cyc	number of cycles for the EM
damp	Not in used
trace	whether to print the EM iterations
plot.opt	plotting the
...	for extra arguments

Value

Returns a list.

Author(s)

Mikis Stasinopoulos

References

Einbeck, J. Darnell R. and Hinde J. (2006) npmlreg: Nonparametric maximum likelihood estimation for random effect models, R package version 0.34

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, gamlssNP

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