Variable Selection and Model Choice in Geoadditive Regression Models [PDF]
, 2007 Model choice and variable selection are issues of major concern in practical regression analyses. We propose a boosting procedure that facilitates both tasks in a class of complex geoadditive regression models comprising spatial effects, nonparametric ...
Kneib, Thomas +2 more
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A-DVM: A Self-Adaptive Variable Matrix Decision Variable Selection Scheme for Multimodal Problems
Entropy, 2020 Artificial Bee Colony (ABC) is a Swarm Intelligence optimization algorithm well known for its versatility. The selection of decision variables to update is purely stochastic, incurring several issues to the local search capability of the ABC.
Marco Antonio Florenzano Mollinetti +3 more
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Multinomial Logit Models with Implicit Variable Selection [PDF]
, 2010 Multinomial logit models which are most commonly used for the modeling of unordered multi-category responses are typically restricted to the use of few predictors. In the high-dimensional case maximum likelihood estimates frequently do not exist. In this
Tutz, Gerhard, Zahid, Faisal Maqbool
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Application of variable selection and dimension reduction on predictors of MSE’s development
Journal of Big Data, 2019 Nature create variables using its character component, and variables are sharing characters from a vary small to relatively large scale. This results, variables to have from a vary different to a more similar character, and leads to have a relation ship.
Habtamu Tilaye Wubetie
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Variable selection in multivariate multiple regression.
PLoS ONE, 2020 IntroductionIn many practical situations, we are interested in the effect of covariates on correlated multiple responses. In this paper, we focus on estimation and variable selection in multi-response multiple regression models.
Asokan Mulayath Variyath, Anita Brobbey
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Identifying Plant Pentatricopeptide Repeat Proteins Using a Variable Selection Method
Frontiers in Plant Science, 2021 Motivation: Pentatricopeptide repeat (PPR), which is a triangular pentapeptide repeat domain, plays an important role in plant growth. Features extracted from sequences are applicable to PPR protein identification using certain classification methods ...
Xudong Zhao +5 more
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Group Variable Selection Methods with Quantile Regression: A Simulation Study. [PDF]
المجلة العراقية للعلوم الاحصائيةIn many cases, covariates have a grouping structure that can be used in the analysis to identify important groups and the significant members of those groups. This paper reviews some group variable selection methods that utilize quantile regression.
Hussein Hashem
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Variable Selection Bias in Classification Trees Based on Imprecise Probabilities [PDF]
, 2005 Classification trees based on imprecise probabilities provide an advancement of classical classification trees. The Gini Index is the default splitting criterion in classical classification trees, while in classification trees based on imprecise ...
Carolin Strobl, Strobl, Carolin
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Spectral variable selection for estimation of soil organic carbon content using mid-infrared spectroscopy [PDF]
, 2022 The non-destructive and rapid estimation of soil total carbon (SOC) content with mid-infrared spectroscopy (MIR, 4000–400 cm−1) will play a vital role in precision agriculture.
Tongqing Liu +9 more
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Variable Selection in Multivariable Regression Using SAS/IML
Journal of Statistical Software, 2002 This paper introduces a SAS/IML program to select among the multivariate model candidates based on a few well-known multivariate model selection criteria. Stepwise regression and all-possible-regression are considered.
Ali A. Al-Subaihi
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