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Generalized additive model for location, scale and shape

Known as: GAMLSS, Generalized Additive Model Location, Scale and Shape (GAMLSS), Generalized additive model for location, scale, and shape 
The Generalized Additive Model for Location, Scale and Shape (GAMLSS) is about statistical modelling and learning. GAMLSS is a modern distribution… Expand
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Papers overview

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2020
2020
We propose a new framework of CatBoost that predicts the entire conditional distribution of a univariate response variable. In… Expand
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2019
2019
For numerous applications it is of interest to provide full probabilistic forecasts, which are able to assign probabilities to… Expand
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2018
2018
We extend Generalized Additive Models for Location, Scale, and Shape (GAMLSS) to regression with functional response. This allows… Expand
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2017
2017
Rigby & Stasinopoulos (2005) introduced generalized additive models for location, scale and shape (GAMLSS) where the response… Expand
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2016
2016
This study aims to model the nonlinear relationship between the daily amount of extreme rainfall and significant predictor… Expand
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2016
2016
We discuss scalar-on-function regression models where all parameters of the assumed response distribution can be modeled… Expand
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2015
2015
This paper presents the design of optimal Bonus-Malus Systems (BMS) using generalized additive models for location, scale and… Expand
2014
2014
The Basel II framework strictly defines the conditions under which financial institutions are authorized to accept real estate as… Expand
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2011
2011
This paper documents the application of the Sichel (SI) generalized additive models for location, scale and shape (GAMLSS) for… Expand
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Highly Cited
2005
Highly Cited
2005
A general class of statistical models for a univariate response variable is presented which we call the generalized additive… Expand