NP.control {gamlss.mx}

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