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Plots Transformations And Regression An Introduction To Graphical Methods Of Diagnostic Regression Analysis
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In this paper, plots transformations and regression is used as an introduction to graphical methods of diagnostic regression analysis, but end up in malicious downloads, instead of reading a good book with a cup of coffee in the afternoon, instead they are facing with some infectious bugs inside their laptop.Abstract:
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Citations
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Journal ArticleDOI
Visualization of Regression Models Using visreg
Patrick Breheny,Woodrow Burchett +1 more
TL;DR: An R package, visreg, is introduced for the convenient visualization of this relationship between an outcome and an explanatory variable via short, simple function calls and provides pointwise condence bands and partial residuals to allow assessment of variability as well as outliers and other deviations from modeling assumptions.
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Visualizing Big Data Outliers Through Distributed Aggregation
TL;DR: This paper presents a new algorithm, called hdoutliers , for detecting multidimensional outliers, based on a distributional model that allows outliers to be tagged with a probability, which reduces the likelihood of false discoveries.
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zoib: An R Package for Bayesian Inference for Beta Regression and Zero/One Inflated Beta Regression
Fang Liu,Yunchuan Kong +1 more
TL;DR: This paper introduces an R package – zoib that provides Bayesian inferences for a class of ZOIB models that can model data with or without inflation at 0 or 1, accommodate clustered and correlated data via latent variables, perform penalized regression as needed, and allow for model comparison via the computation of the DIC criterion.
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The Dimensions of Experiential Learning in the Management of Activity Load
TL;DR: It is found that heavier activity loads exact a smaller toll on performance when firms have larger and more homogeneous stocks of prior experience, however, when firms’ prior experience is more rapidly paced or successful, the toll of heavier activity load on performance grows.
Journal ArticleDOI
Count data in biology—Data transformation or model reformation?
TL;DR: No consensus could be found in the literature regarding a procedure to back‐transform the coefficient estimates obtained from linear models performed on transformed datasets, and this lack of consistency among coefficient estimates constitutes a major argument for model reformation over data transformation in biology.
References
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Journal ArticleDOI
Visualization of Regression Models Using visreg
Patrick Breheny,Woodrow Burchett +1 more
TL;DR: An R package, visreg, is introduced for the convenient visualization of this relationship between an outcome and an explanatory variable via short, simple function calls and provides pointwise condence bands and partial residuals to allow assessment of variability as well as outliers and other deviations from modeling assumptions.
Journal ArticleDOI
Visualizing Big Data Outliers Through Distributed Aggregation
TL;DR: This paper presents a new algorithm, called hdoutliers , for detecting multidimensional outliers, based on a distributional model that allows outliers to be tagged with a probability, which reduces the likelihood of false discoveries.
Journal ArticleDOI
zoib: An R Package for Bayesian Inference for Beta Regression and Zero/One Inflated Beta Regression
Fang Liu,Yunchuan Kong +1 more
TL;DR: This paper introduces an R package – zoib that provides Bayesian inferences for a class of ZOIB models that can model data with or without inflation at 0 or 1, accommodate clustered and correlated data via latent variables, perform penalized regression as needed, and allow for model comparison via the computation of the DIC criterion.
Posted Content
The Dimensions of Experiential Learning in the Management of Activity Load
TL;DR: It is found that heavier activity loads exact a smaller toll on performance when firms have larger and more homogeneous stocks of prior experience, however, when firms’ prior experience is more rapidly paced or successful, the toll of heavier activity load on performance grows.
Journal ArticleDOI
Count data in biology—Data transformation or model reformation?
TL;DR: No consensus could be found in the literature regarding a procedure to back‐transform the coefficient estimates obtained from linear models performed on transformed datasets, and this lack of consistency among coefficient estimates constitutes a major argument for model reformation over data transformation in biology.