Results 31 to 40 of about 56,202 (281)
F1000Research, 2021 Background: Multicollinearity greatly affects the Maximum Likelihood Estimator (MLE) efficiency in both the linear regression model and the generalized linear model. Alternative estimators to the MLE include the ridge estimator, the Liu estimator and the
Olukayode Adebimpe +4 more
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Ordinal Ridge Regression with Categorical Predictors [PDF]
, 2011 In multi-category response models categories are often ordered. In case of ordinal response models, the usual likelihood approach becomes unstable with ill-conditioned predictor space or when the number of parameters to be estimated is large relative to ...
Zahid, Faisal Maqbool
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Journal of Advanced Research in Natural and Applied Sciences, 2020 The determination of leverage observations have been frequently investigated through ordinary least squares and some biased estimators proposed under the multicollinearity problem in the linear regression models.
Tuğba Söküt
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Robust Permutation Tests for Penalized Splines
Stats, 2022 Penalized splines are frequently used in applied research for understanding functional relationships between variables. In most applications, statistical inference for penalized splines is conducted using the random effects or Bayesian interpretation of ...
Nathaniel E. Helwig
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Feature Extraction in Signal Regression: A Boosting Technique for Functional Data Regression [PDF]
, 2007 Main objectives of feature extraction in signal regression are the improvement of accuracy of prediction on future data and identification of relevant parts of the signal. A feature extraction procedure is proposed that uses boosting techniques to select
Gertheiss, Jan, Tutz, Gerhard
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Structured penalties for functional linear models---partially empirical eigenvectors for regression [PDF]
, 2011 One of the challenges with functional data is incorporating spatial structure, or local correlation, into the analysis. This structure is inherent in the output from an increasing number of biomedical technologies, and a functional linear model is often ...
Feng, Ziding +2 more
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Generalized ridge estimator in negative binomial regression model
Journal of Physics: Conference Series, 2021 Abstract The ridge estimator has been consistently demonstrated to be an attractive shrinkage method to reduce the effects of multicollinearity. The negative binomial regression model (NBRM) is a well-known model in application when the response variable is a count data with overdispersion.
Nadwa Khazaal Rashad +2 more
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Boosting Correlation Based Penalization in Generalized Linear Models [PDF]
, 2007 In high dimensional regression problems penalization techniques are a useful tool for estimation and variable selection. We propose a novel penalization technique that aims at the grouping effect which encourages strongly correlated predictors to be in ...
Tutz, Gerhard, Ulbricht, Jan
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An adaptive Ridge procedure for L0 regularization [PDF]
, 2015 Penalized selection criteria like AIC or BIC are among the most popular methods for variable selection. Their theoretical properties have been studied intensively and are well understood, but making use of them in case of high-dimensional data is ...
Frommlet, Florian, Nuel, Gregory
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The General Linear Test in the Ridge Regression [PDF]
Communications for Statistical Applications and Methods, 2014 We derive a test statistic for the general linear test in the ridge regression model. The exact distribution for the test statistic is too difficult to derive; therefore, we suggest an approximate reference distribution. We use numerical studies to verify that the suggested distribution for the test statistic is appropriate. A asymptotic result for the
Whasoo Bae, Minji Kim, Choongrak Kim
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