Results 21 to 30 of about 4,923 (258)
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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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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Robust and Sparse Regression via γ-Divergence
Entropy, 2017 In high-dimensional data, many sparse regression methods have been proposed. However, they may not be robust against outliers. Recently, the use of density power weight has been studied for robust parameter estimation, and the corresponding divergences ...
Takayuki Kawashima, Hironori Fujisawa
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Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To clarify the clinical relevance of dopamine transporter single‐photon emission computed tomography (DAT‐SPECT) abnormalities in amyotrophic lateral sclerosis (ALS), with a prespecified focus on sex‐stratified associations with disease progression and short‐term prognosis.
Tomoya Kawazoe +7 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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White Matter and Perivascular Imaging Changes in Alzheimer's Disease and Cerebral Amyloid Angiopathy
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Peak‐width of skeletonized mean diffusivity (PSMD) and diffusion tensor imaging–analysis along the perivascular space (DTI‐ALPS), reflecting white matter integrity and glymphatic function, are altered in Alzheimer's disease (AD).
Debina Laishram +3 more
wiley +1 more source