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Analyzing the Relationship Between Meteorological Elements and Criteria Atmospheric Pollutants in Tabriz Using Statistical Modeling [PDF]
علوم محیطیIntroduction: The rapid increase in population, growth of urbanization and industrialization in recent years, which is generally associated with an increase in demand and energy consumption, and as a result, an increase in pollutant emission sources, has
Parisa Kahrari +3 more
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Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 2017 Regression models used to explore the importance of several explanatory variables in estimation, classification and analytical tools play an efficient role for many data analysis.
Betül Kan Kılınç, Mustafa Çavuş
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Network reconstruction using nonparametric additive ODE models. [PDF]
PLoS ONE, 2014 Network representations of biological systems are widespread and reconstructing unknown networks from data is a focal problem for computational biologists.
James Henderson, George Michailidis
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gamboostLSS: An R Package for Model Building and Variable Selection in the GAMLSS Framework
Journal of Statistical Software, 2016 Generalized additive models for location, scale and shape are a flexible class of regression models that allow to model multiple parameters of a distribution function, such as the mean and the standard deviation, simultaneously.
Benjamin Hofner +2 more
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Data‐adaptive additive modeling
Statistics in Medicine, 2018 In this paper, we consider fitting a flexible and interpretable additive regression model in a data‐rich setting. We wish to avoid pre‐specifying the functional form of the conditional association between each covariate and the response, while still retaining interpretability of the fitted functions.
Ashley Petersen, Daniela Witten
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Fused Lasso Additive Model [PDF]
Journal of Computational and Graphical Statistics, 2016 We consider the problem of predicting an outcome variable using p covariates that are measured on n independent observations, in a setting in which additive, flexible, and interpretable fits are desired. We propose the fused lasso additive model (FLAM), in which each additive function is estimated to be piecewise constant with a small number of ...
Petersen, Ashley +2 more
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Additive and non-additive genetic effects of humoral immune traits in Japanese quail
Journal of Applied Poultry Research, 2022 SUMMARY: In breeding programs, using appropriate models to estimate the variance components with high accuracy is essential. Considering the non-additive genetic effects along with additive effects in evaluation analysis models can be effective in ...
H. Faraji-Arough +3 more
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Functional Generalized Additive Models [PDF]
Journal of Computational and Graphical Statistics, 2014 We introduce the functional generalized additive model (FGAM), a novel regression model for association studies between a scalar response and a functional predictor. We model the link-transformed mean response as the integral with respect to t of F{X(t), t} where F(·,·) is an unknown regression function and X(t) is a functional covariate.
Mathew W, McLean +4 more
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BayesX: Analyzing Bayesian Structural Additive Regression Models
Journal of Statistical Software, 2005 There has been much recent interest in Bayesian inference for generalized additive and related models. The increasing popularity of Bayesian methods for these and other model classes is mainly caused by the introduction of Markov chain Monte Carlo (MCMC)
Andreas Brezger +2 more
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Вестник Самарского университета: Естественнонаучная серия, 2023 For modeling in time series, models with fractional differences are widely used. The best known model is the ARFIMA (autoregressive fractionally integrated moving average) model.
Dmitriy V. Ivanov
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