| Title: | Quantile Maximization Likelihood Estimation and Bayesian Ex-Gaussian Estimation |
| Version: | 0.1.2 |
| Description: | Presents two methods to estimate the parameters 'mu', 'sigma', and 'tau' of an ex-Gaussian distribution. Those methods are Quantile Maximization Likelihood Estimation ('QMLE') and Bayesian. The 'QMLE' method allows a choice between three different estimation algorithms for these parameters : 'neldermead' ('NEMD'), 'fminsearch' ('FMIN'), and 'nlminb' ('NLMI'). For more details about the methods you can refer at the following list: Brown, S., & Heathcote, A. (2003) <doi:10.3758/BF03195527>; McCormack, P. D., & Wright, N. M. (1964) <doi:10.1037/h0083285>; Van Zandt, T. (2000) <doi:10.3758/BF03214357>; El Haj, A., Slaoui, Y., Solier, C., & Perret, C. (2021) <doi:10.19139/soic-2310-5070-1251>; Gilks, W. R., Best, N. G., & Tan, K. K. C. (1995) <doi:10.2307/2986138>. |
| License: | GPL-2 |
| Encoding: | UTF-8 |
| LazyLoad: | true |
| RoxygenNote: | 7.2.3 |
| Imports: | pracma, stats, nloptr, invgamma, dlm, fitdistrplus, gamlss.dist |
| NeedsCompilation: | no |
| Packaged: | 2023-10-06 06:57:48 UTC; jean |
| Suggests: | testthat (≥ 3.0.0) |
| Config/testthat/edition: | 3 |
| Author: | Yousri SLAOUI 
[aut],
Abir EL HAJ [aut,
ctb],
Alandra ZAKKOUR [aut],
Caroline BORDES [aut, ctb],
Cyril PERRET
[aut],
Jean DUMONCEL
[aut, cre] |
| Maintainer: | Jean DUMONCEL <jean.dumoncel@univ-poitiers.fr> |
| Repository: | CRAN |
| Date/Publication: | 2023-10-06 07:20:02 UTC |
Bayesian Ex-gaussian Estimate
Description
Estimates the mu, sigma, and tau parameters of an ex-Gaussian distribution using a bayesian method.
Usage
BayesianExgaussian(n, x, nSamples = 5000, Ti = 2500)
Arguments
n |
the data size |
x |
the data. Must be a vector, with no missing values |
nSamples |
number of Samples |
Ti |
burn-in |
Value
BayesianExgaussian() returns an object "theta" which is a list with components: estimates of mu, sigma, and tau
References
Brown, S., & Heathcote, A. (2003). QMLE: Fast, robust, and efficient estimation of distribution functions based on quantiles. Behavior Research Methods, Instruments, & Computers, 35, 485-492.
McCormack, P. D., & Wright, N. M. (1964). The positive skew observed in reaction time distributions. Canadian Journal of Psychology/Revue canadienne de psychologie, 18, 43-51.
Van Zandt, T. (2000). How to fit a response time distribution. Psychonomic Bulletin & Review, 7, 424-465.
El Haj, A., Slaoui, Y., Solier, C., & Perret, C. (2021). Bayesian Estimation of The Ex-Gaussian distribution. Statistics, Optimization & Information Computing, 9(4), 809-819.
Gilks, W. R., Best, N. G., & Tan, K. K. C. (1995). Adaptive rejection Metropolis sampling within Gibbs sampling. Journal of the Royal Statistical Society: Series C (Applied Statistics), 44, 455-472.
Examples
library(gamlss.dist)
set.seed(2703)
data<-rexGAUS(n=100, mu = 500, sigma = 150, nu = 100)
BayesianExgaussian(n = 100, x = data)
Ex-Gaussian Quantile Maximum Likelihood Estimate
Description
Estimates the mu, sigma, and tau parameters of an ex-Gaussian distribution. 3 different algorithms can be used : neldermead ('NEMD'), fminsearch ('FMIN') and nlminb ('NLMI').
Usage
QMLEEstim(y, func)
Arguments
y |
the data. Must be a vector with no missing values |
func |
the function selected for the estimation. 'NEMD' for neldermead, 'FMIN' for fminsearch, and 'NLMI' for nlminb. |
Value
QMLEEstim() returns an object "valEstim" which is a list with components: estimates of mu, sigma, and tau
References
Brown, S., & Heathcote, A. (2003). QMLE: Fast, robust, and efficient estimation of distribution functions based on quantiles. Behavior Research Methods, Instruments, & Computers, 35, 485-492.
McCormack, P. D., & Wright, N. M. (1964). The positive skew observed in reaction time distributions. Canadian Journal of Psychology/Revue canadienne de psychologie, 18, 43-51.
Van Zandt, T. (2000). How to fit a response time distribution. Psychonomic Bulletin & Review, 7, 424-465.
El Haj, A., Slaoui, Y., Solier, C., & Perret, C. (2021). Bayesian Estimation of The Ex-Gaussian distribution. Statistics, Optimization & Information Computing, 9(4), 809-819.
Gilks, W. R., Best, N. G., & Tan, K. K. C. (1995). Adaptive rejection Metropolis sampling within Gibbs sampling. Journal of the Royal Statistical Society: Series C (Applied Statistics), 44, 455-472.
Examples
library(gamlss.dist)
set.seed(2703)
data<-rexGAUS(n=100, mu = 500, sigma = 150, nu = 100)
QMLEEstim(data, 'NEMD')