Open AccessBook
Regression Analysis: Theory, Methods, and Applications
Ashish Sen,Muni S. Srivastava +1 more
TLDR
An up-to-date, rigorous, and lucid treatment of the theory, methods, and applications of regression analysis, and thus ideally suited for those interested in the theory as well as those whose interests lie primarily with applications.Abstract:
An up-to-date, rigorous, and lucid treatment of the theory, methods, and applications of regression analysis, and thus ideally suited for those interested in the theory as well as those whose interests lie primarily with applications. It is further enhanced through real-life examples drawn from many disciplines, showing the difficulties typically encountered in the practice of regression analysis. Consequently, this book provides a sound foundation in the theory of this important subject.read more
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Journal ArticleDOI
Penalized Regressions: The Bridge versus the Lasso
TL;DR: It is shown that the bridge regression performs well compared to the lasso and ridge regression, and is demonstrated through an analysis of a prostate cancer data.
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Towards a standard for pointing device evaluation, perspectives on 27 years of Fitts' law research in HCI
TL;DR: This paper makes seven recommendations to HCI researchers wishing to construct Fitts' law models for either movement time prediction, or for the comparison of conditions in an experiment that support the methods described in the recent ISO 9241-9 standard on the evaluation of pointing devices.
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Identification and Review of Sensitivity Analysis Methods
H. Christopher Frey,Sumeet Patil +1 more
TL;DR: Identification and qualitative comparison of sensitivity analysis methods that have been used across various disciplines, and that merit consideration for application to food-safety risk assessment models, are presented.
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Using wavelet network in nonparametric estimation
TL;DR: Algorithms for wavelet network construction are proposed for the purpose of nonparametric regression estimation and particular attentions are paid to sparse training data so that problems of large dimension can be better handled.
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A statistical overview of standard (IUPAC and ACS) and new procedures for determining the limits of detection and quantification: Application to voltammetric and stripping techniques (Technical Report)
TL;DR: In this paper, the upper limit approach, ULA, is proposed to calculate the upper confidence limit of an individual blank signal using a critical value of the tdistribution and standard error of estimate (residual standard deviation) of regression.