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Uncertainty Quantification Techniques in Statistics (Paperback, 2020)

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About this product

Product Information

Uncertainty quantification (UQ) is a mainstream research topic in applied mathematics and statistics. To identify UQ problems, diverse modern techniques for large and complex data analyses have been developed in applied mathematics, computer science, and statistics. This Special Issue of Mathematics (ISSN 2227-7390) includes diverse modern data analysis methods such as skew-reflected-Gompertz information quantifiers with application to sea surface temperature records, the performance of variable selection and classification via a rank-based classifier, two-stage classification with SIS using a new filter ranking method in high throughput data, an estimation of sensitive attribute applying geometric distribution under probability proportional to size sampling, combination of ensembles of regularized regression models with resampling-based lasso feature selection in high dimensional data, robust linear trend test for low-coverage next-generation sequence data controlling for covariates, and comparing groups of decision-making units in efficiency based on semiparametric regression.

Product Identifiers

PublisherMdpi Ag

ISBN-139783039285464

eBay Product ID (ePID)6046398805

Product Key Features

SubjectBiology

Publication Year2020

Number of Pages128 Pages

Publication NameUncertainty Quantification Techniques in Statistics

LanguageEnglish

TypeTextbook

FormatPaperback

Dimensions

Item Height244 mm

Item Weight286 g

Item Width170 mm