Results 11 to 20 of about 280,435 (260)

Building flexible regression models: including the Birnbaum-Saunders distribution in the gamlss package

open access: yesSemina: Ciências Exatas e Tecnológicas, 2021
Generalized additive models for location, scale and shape (GAMLSS) are a very flexible statistical modeling framework, being an important generalization of the well-known generalized linear models and generalized additive models.
Fernanda V. Roquim   +5 more
doaj   +1 more source

Generalized Additive Models [PDF]

open access: yesStatistical Science, 1984
The classical linear regression model expresses the response vector Y as a function of the predictor variables \(X_ i\) through the model \(Y=\sum_{i}X_ i\beta_ i+e\), where the \(X_ i\) are observed, the \(\beta_ i\) are estimated by least squares or some other technique, e is the vector of errors.
Hastie, Trevor, Tibshirani, Robert
openaire   +3 more sources

Mapping spatial patterns of plant species based on machine-learning and regression models [PDF]

open access: yesDesert, 2022
Various statistical techniques have been used for species distribution modeling that attempt to predict the occurrence of a given species with respect to environmental conditions.
H. Keshtkar, P. Pourmohammad
doaj   +1 more source

Analyzing Temporal Trends of Urban Evaporation Using Generalized Additive Models

open access: yesLand, 2022
This study aimed to gain new insights into urban hydrological balance (in particular, the evaporation from paved surfaces). Hourly evaporation data were obtained simultaneously from two high-resolution weighable lysimeters.
Basem Aljoumani   +4 more
doaj   +1 more source

Application of Machine Learning Techniques to High-Dimensional Clinical Data to Forecast Postoperative Complications. [PDF]

open access: yesPLoS ONE, 2016
OBJECTIVE:To compare performance of risk prediction models for forecasting postoperative sepsis and acute kidney injury. DESIGN:Retrospective single center cohort study of adult surgical patients admitted between 2000 and 2010.
Paul Thottakkara   +6 more
doaj   +1 more source

evgam: An R Package for Generalized Additive Extreme Value Models

open access: yesJournal of Statistical Software, 2022
This article introduces the R package evgam. The package provides functions for fitting extreme value distributions. These include the generalized extreme value and generalized Pareto distributions.
Benjamin D. Youngman
doaj   +1 more source

Tariff Analysis in Automobile Insurance: Is It Time to Switch from Generalized Linear Models to Generalized Additive Models?

open access: yesMathematics, 2023
Generalized Linear Models (GLMs) are the standard tool used for pricing in the field of automobile insurance. Generalized Additive Models (GAMs) are more complex and computationally intensive but allow taking into account nonlinear effects without the ...
Zuleyka Díaz Martínez   +2 more
doaj   +1 more source

High-resolution estimates of tuberculosis incidence among non-U.S.-born persons residing in the United States, 2000–2016

open access: yesEpidemics, 2020
In the United States, new tuberculosis cases are increasingly concentrated within non-native-born populations. We estimated trends and differences in tuberculosis incidence rates for the non-U.S.-born population, at a resolution unobtainable from raw ...
Andrew N. Hill   +3 more
doaj   +1 more source

Generalized Additive Models: An Introduction with R

open access: yesJournal of Statistical Software, 2006
s not available for ...
John Maindonald
doaj   +1 more source

Principal components and generalized linear modeling in the correlation between hospital admissions and air pollution

open access: yesRevista de Saúde Pública, 2014
OBJECTIVE To analyze the association between concentrations of air pollutants and admissions for respiratory causes in children. METHODS Ecological time series study.
Juliana Bottoni de Souza   +3 more
doaj   +1 more source

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