Results 21 to 30 of about 4,642 (256)
Spatio-Temporal Forecasting of Global Horizontal Irradiance Using Bayesian Inference
Applied Sciences, 2022 Accurate global horizontal irradiance (GHI) forecasting promotes power grid stability. Most of the research on solar irradiance forecasting has been based on a single-site analysis.
Caston Sigauke +2 more
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Mapping wind erosion hazard with regression-based machine learning algorithms
Scientific Reports, 2020 Land susceptibility to wind erosion hazard in Isfahan province, Iran, was mapped by testing 16 advanced regression-based machine learning methods: Robust linear regression (RLR), Cforest, Non-convex penalized quantile regression (NCPQR), Neural network ...
Hamid Gholami +3 more
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Monotonicity is a key feature of genotype-phenotype maps
Frontiers in Genetics, 2013 It was recently shown that monotone gene action, i.e. order-preservation between allele content and corresponding genotypic values in the mapping from genotypes to phenotypes, is a prerequisite for achieving a predictable parent-offspring relationship ...
Arne Bjørke Gjuvsland +4 more
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Mathematics, 2022 Clustered and heterogeneous interval-censored data occur in many fields such as medical studies. For example, in a migraine study with the Netherlands Twin Registry, the information including time to diagnosis of migraine and gender was collected for ...
Xifen Huang, Jinfeng Xu
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bsamGP: An R Package for Bayesian Spectral Analysis Models Using Gaussian Process Priors
Journal of Statistical Software, 2019 The Bayesian spectral analysis model (BSAM) is a powerful tool to deal with semiparametric methods in regression and density estimation based on the spectral representation of Gaussian process priors. The bsamGP package for R provides a comprehensive set
Seongil Jo +3 more
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Testing regression monotonicity in econometric models [PDF]
Econometric Theory, 2012 Monotonicity is a key qualitative prediction of a wide array of economic models derived via robust comparative statics. It is therefore important to design effective and practical econometric methods for testing this prediction in empirical analysis.
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Efficient computation of locally monotonic regression [PDF]
Revista de Ingeniería, 1996 Locally monotonic regression provides a way of smoothing signals under the smoothness criterion of local monotonicity, which sets a restriction on how often a signal may change trend (increasing to decreasing, or vice versa). So far, the applicability of locally monotonic regression has been limited by the high computational costs of the available ...
Ramiro de la Vega +1 more
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Monotone Nonparametric Regression
The Annals of Statistics, 1988 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Journal of Applied Mathematics, 2014 The imputation of missing data is often a crucial step in the analysis of survey data. This study reviews typical problems with missing data and discusses a method for the imputation of missing survey data with a large number of categorical variables ...
Machelle D. Wilson, Kerstin Lueck
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Bayesian spatial monotonic multiple regression [PDF]
Biometrika, 2018 We consider monotonic, multiple regression for a set of contiguous regions (lattice data). The regression functions permissibly vary between regions and exhibit geographical structure. We develop new Bayesian non-parametric methodology which allows for both continuous and discontinuous functional shapes and which are estimated using marked point ...
Rohrbeck, Christian +2 more
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