Minimax rate of testing in sparse linear regression [PDF]
, 2018 We consider the problem of testing the hypothesis that the parameter of linear regression model is 0 against an s-sparse alternative separated from 0 in the 2-distance.
Tsybakov, Alexandre +4 more
core
Migration and students' performance: detecting geographical differences following a curves clustering approach. [PDF]
J Appl Stat, 2022 Boscaino G, Sottile G, Adelfio G.
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Tweedie Compound Poisson Models with Covariate-Dependent Random Effects for Multilevel Semicontinuous Data. [PDF]
Entropy (Basel), 2023 Ma R, Islam MD, Hasan MT, Jørgensen B.
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The more data, the better? Demystifying deletion-based methods in linear regression with missing data. [PDF]
Stat Interface, 2022 Xu T, Chen K, Li G.
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Taylor quasi-likelihood for limited generalized linear models. [PDF]
J Appl Stat, 2021 Guo G.
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Modified maximum likelihood estimator under the Jones and Faddy's skew t-error distribution for censored regression model. [PDF]
J Appl Stat, 2021 Acitas S +3 more
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On the determination coefficient in robust regression
, 2000 In simple linear regression the determination coefficient tells us which percentage of the variance of the response variable is explained by the fitted linear mapping of the explanatory variable.
Dirk Tasche
core
Analysis of Longitudinal Binomial Data with Positive Association between the Number of Successes and the Number of Failures: An Application to Stock Instability Study. [PDF]
Entropy (Basel), 2022 Zhang X, Yan G, Ma R, Li J.
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Optimal ridge estimation in the restricted logistic semiparametric regression models using generalized cross-validation. [PDF]
J Appl StatRoozbeh M.
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Distributed robust estimation and inference with contaminated data. [PDF]
Electron J StatZhang P, Zhou WX, Ren Z.
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