| QMLEEstim {ExGaussEstim} | R Documentation |
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')