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The Team

  • Prof. Mikis Stasinopoulos (ABM Analytics Ltd, UK): development and maintenance of software.
  • Dr. Bob Rigby: development of distributions and theory.
  • Dr. Vlasios Voudouris (ABM Analytics Ltd, UK):  Development and fusion of GAMLSS and agent-based models for long-term scenarios and short-term forecasts, particularly their application at  oil, gas and electricity market dynamics. Vlasios also uses GAMLSS as a component of the products and services offered by ABM Analytics Ltd.
  • Prof. Paul Eilers (Erasmus University, Netherlands): giving valuable advice on smoothing and statistical modelling in general.
  • Prof. Gillian Heller (Macquarie University, Australia): development and applications in actuarial statistics.
  • Dr Nikolaos Georgikopoulos (KEPE, Greece, and  Stern School of Business, New York): development, applications and consultant in finance and banking (risk management).
  • Dr. Majid Djennad (Public Health England): development of   GAMLSS time series
  • Dr. Daniil Kiose : (Kingston University, UK) GAMLSS implementation in  Java  and applications  in finance and  energy.
  • Dr. Andreas Mayr (Institut für Medizininformatik, Biometrie und Epidemiologie, Friedrich-Alexander-Universität Erlangen-Nürnberg) : boosting and GAMLSS.
  • Dr. Fernanda De Bastiani (Federal University of Pernambuco, Brazil and Pontificia Universidad Catolica de Chile, Santiago):  development of   GAMLSS spatial.
  • Dr Marco Enea ( Istituto per l’Ambiente Marino Costiero, Italy): development of GAMLSS inflated distributions package.
  • Dr. Luiz Nakamura (University of São Paulo, Brazil): development of the extension of the Birnbaum-Saunders distribution within the GAMLSS.

 

Design

The GAMLSS logo, several images from the current website and the front cover of the book Flexible Regression and smoothing: Using GAMLSS in R are designed by Harry Stasinopoulos of the Keston Cobblers Club

 

Contributors

The original GAMLSS implementation was done in GLIM by Mikis Stasinopoulos and Bob Rigby. The translation from GLIM to R was done in the early 2002 by Mikis Stasinopoulos, Bob Rigby and Popi Akanziliotou. For the more current versions the following people have voluntarily contributed to the GAMLSS software:

  • Elaine Borghie contributed in the improvement of functions centiles.pred()centiles.split() and Q.stats()
  • Paul Eilers contributed in the creation of the functions scattersmooth(), pb(), cy() and pvc() and in the package gamlss.demo
  • Steve Ellison contributed to the centiles() function
  • Michael Hohle corrected the function gamlssNP()
  • Larisa Kosidou contributed in the improvement of the package gamlss.demo
  • Brian Marx contributed to the package gamlss.demo
  • Nicoleta Mortan contributed into the creation of the package gamlss.cens
  • Raydonal Ospina contributed the BEOI and BEZI distributions for package gamlss.dist
  • Konstantinos Pateras contributed by creating the nice interfaces in the package gamlss.demo

 

The following people whose function(s) have been adapted for the GAMLSS software:

  • Gareth Amber for his fractional polynomial function which the gamlss fp() function is based.
  • John Chambers and Trevor Hastie for their R function step.gam() on which the gamlss function stepGAIC.CH() is based
  • Jochen Einbeck, Ross Darnell and John Hinde for their functions alldist() and allvc() from the package npmlreg on which the gamlss.mx function gamlssNP() is based
  • Trevor Hastie for the function random()
  • Jim Lindsey and Philippe Lambert for their function stableglm() in the package stable on which the gamlss.nl function nlgamlss() is based
  • Brian Ripley for his function nnet() to which the gamlss function nn() provides an interface and for the function multinom() which is used in our function gamlssMX()
  • Stefan van Buuren for his original worm plot function on which the gamlss wp() function is based.
  • Venables and Ripley for their R function stepAIC() on which the gamlss function stepGAIC.VR() is based.
  • Simon Wood for his function gam() to which the gamlss function ga() provides an interface.

Acknowledgement

We also like to thank the following people who have contributed by suggesting changes or by reporting bugs:

  • Christian Kiffner for suggesting changes for the function term.plot()
  • Albert Wong for suggesting changes to the function lpred() applied to interval response variables.
  • Tim Cole for several suggestions for improvement of the gamlss software.
  • Huiqi Pan for several suggestions to improve centile estimation in gamlss.
  • Willem Vervoort for reporting the problems for calling gamlss() within other functions.