c(
person("Claster", "William B.", email = "william108@gmail.com", role = "aut"),
person("Philip", "Sallis", email = "philip.sallis@aut.ac.nz", role = "aut"),
person("Nhat Cuong", "Pham", email = "acmetal74@gmail.com", role = c("aut", "cre")))
Claster William B. [aut],
Philip Sallis [aut],
Nhat Cuong Pham [aut, cre]

Statistical Modelling for Asymmetric Exponential Power
Distribution
Developed for Computing the probability density function,
cumulative distribution function, random generation, estimating the parameters
of asymmetric exponential power distribution, and robust regression analysis
with error term that follows asymmetric exponential power distribution.

person('Mahdi', 'Teimouri', email = 'teimouri@aut.ac.ir', role = c('aut', 'cre', 'cph', 'ctb'), comment = c(ORCID = '0000-0002-5371-9364'))
Mahdi Teimouri [aut, cre, cph, ctb]
(<https://orcid.org/0000-0002-5371-9364>)
Developed for Computing the probability density function, cumulative
distribution function, random generation, estimating the parameters of asymmetric
exponential power distribution, and robust regression analysis with error
term that follows asymmetric exponential power distribution. The asymmetric
exponential power distribution studied here is a special case of that introduced
by Dongming and Zinde-Walsh (2009) <doi:10.1016/j.jeconom.2008.09.038>.

Functions, data sets, examples and vignettes for the book
Christian Kleiber and Achim Zeileis (2008),
Applied Econometrics with R, Springer-Verlag, New York.
R (>= 2.5.0), stats, car, lmtest, sandwich, strucchange, survival, zoo
boot, dynlm, foreign, ineq, KernSmooth, lattice, MASS, nlme,
nnet, np, plm, pscl, quantreg, ROCR, systemfit, tseries, urca

boot, dynlm, foreign, ineq, KernSmooth, lattice, MASS, nlme,
nnet, np, plm, pscl, quantreg, ROCR, sampleSelection, systemfit, tseries, urca

Functions, data sets, examples and vignettes for the book
Christian Kleiber and Achim Zeileis (2008),
Applied Econometrics with R, Springer-Verlag, New York.
(Table of contents: 1. Introduction, 2. Basics, 3. Linear Regression,
4. Diagnostics and Alternative Methods of Regression,
5. Models of Microeconometrics, 6. Time Series,
7. Programming Your Own Analysis)