BayesianBoot {gamlss.foreach}

Non parametric and Bayesian Bootstrapping for GAMLSS models

Description

The function takes a GAMLSS fitted model and bootstrap it to create B bootstrap samples.

Usage

NonParametricBoot(obj, data = NULL, B = 100, newdata = NULL)

BayesianBoot(obj, data = NULL, B = 100, newdata = NULL)

Arguments

obj

a gamlss fitted model

data

a data frame

B

the number of boostrap samples

newdata

new data for predictAll()

Details

The function NonParametric() perform non-parametric bootstraping, Efron and Tibshirani (1993) while the function BayesianBoot() perform Bayesian bootstrap Rubin (1981)

Value

An Bayesian.boot object with elements

boot

the bootstrap samples

B

the required number of boostraps

trueB

the actual number of boostraps

par

the distribution parameters

orig.coef

the fitted coeficients from the GAMLSS model

orig.call

the call from the GAMLSS model

Author(s)

Mikis Stasinopoulos, [e-mail]

References

Efron, B. and Tibshirani, R, (1993), An introduction to the bootstrap, Chapman and Hall New York, Monographs on statistics and applied probability, vulume 57.

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, doi:10.1201/9780429298547. An older version can be found in https://www.gamlss.com/.

Rubin, D. B. (1981) the bayesian bootstrap. The annals of statistics, pp. 130-134.

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, doi:10.18637/jss.v023.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. doi:10.1201/b21973

Stasinopoulos, M. D., Rigby, R. A., and De Bastiani F., (2018) GAMLSS: a distributional regression approach, Statistical Modelling, Vol. 18, pp, 248-273, SAGE Publications Sage India: New Delhi, India. doi:10.1177/1471082X18759144

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

See Also

gamlss

Examples

m1 <-gamlss(y~x+qrt, data=aids, family=NBI())
registerDoParallel(cores = 2)
B1 <- BayesianBoot(m1)
summary(B1)
plot(B1)
B2 <- NonParametricBoot(m1)
stopImplicitCluster()
summary(B2)
plot(B2)