PEMODELAN PRODUKTIVITAS PADI DENGAN MENGGUNAKAN GENERALIZED ADDITIVE MODELS DI PROVINSI BANTEN
Jurnal Lebesgue, 2020 Tujuan dari penelitian ini adalah untuk melakukan pemodelan produktivitas padi. Sumber data yang digunakan dalam penelitian ini adalah data produktivitas padi, penggunaan pupuk, penggunaan benih, sistem tanam, serangan OPT, dampak perubahan iklim, dan ...
Wahyudi Manurung, Muhammad Fajar, Noviar
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SPATIAL REGRESSION APPROACH TO MODELLING POVERTY IN JAVA ISLAND 2022
BarekengGeographically Weighted Regression (GWR) model is a powerful tool for analyzing spatial patterns in data. However, the standard form of a spatial model that uses a single bandwidth calibration may be unrealistic because the response-predictor ...
Maria A. Hasiholan Siallagan +1 more
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Annals of Forest Science, 2023 Key message The non-linear seemingly unrelated regression mixed-effects model (NSURMEM) and generalized additive model (GAM) were applied for the first time in crown width (CW) additive models of larch (Larix gmelinii Rupr.), birch (Betula platyphylla ...
Junjie Wang +5 more
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Semina: 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
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Normal-Mixture-of-Inverse-Gamma Priors for Bayesian Regularization and Model Selection in Structured Additive Regression Models [PDF]
, 2010 In regression models with many potential predictors, choosing an appropriate subset of covariates and their interactions at the same time as determining whether linear or more flexible functional forms are required is a challenging and important task. We
Scheipl, Fabian
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Penalized additive regression for space-time data: a Bayesian perspective [PDF]
, 2003 We propose extensions of penalized spline generalized additive models for analysing space-time regression data and study them from a Bayesian perspective.
Stefan Lang +5 more
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Generalized Monotonic Regression Based on B-Splines with an Application to Air Pollution Data [PDF]
, 2005 In many studies where it is known that one or more of the certain covariates have monotonic effect on the response variable, common fitting methods for generalized additive models (GAM) may be affected by a sparse design and often generate implausible ...
Leitenstorfer, Florian, Tutz, Gerhard
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Using generalized estimating equations with regression splines to improve analysis of butterfly transect data [PDF]
, 2008 Surveying animal populations is an important aspect of wildlife management. Distinguishing trend from random fluctuations and quantifying trend are key goals in any analysis.
Brewer, Ciara
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Model selection in generalised structured additive regression models [PDF]
, 2007 In recent years data sets have become increasingly more complex requiring more flexible instruments for their analysis. Such a flexible instrument is regression analysis based on a structured additive predictor which allows an appropriate modelling for ...
Belitz, Christiane
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Modelling stem cell differentiation related processes—A practical overview for biologists
FEBS Letters, EarlyView.Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar +4 more
wiley +1 more source