Results 71 to 80 of about 163,142 (181)
Shifted Liu-Type Estimator in The Linear Regression
Jurnal Matematika, Statistika dan Komputasi, 2022 The methods to solve the problem of multicollinearity have an important issue in the linear regression. The Liu-type estimator is one of these methods used to reduce its effect. This estimator is an estimator with two parameters denoted and . Kurnaz and Akay (2015) [6] introduced a new approach for the Liu-type estimator and called it new Liu-type (NL)
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Maximum Likelihood and the Bootstrap for Nonlinear Dynamic Models [PDF]
We provide a unified framework for analyzing bootstrapped extremum estimators of nonlinear dynamic models for heterogeneous dependent stochastic processes.
Halbert White, Sílvia Gonçalves
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Estimating Shrinkage Parameter of Generalized Liu Estimator in Logistic Regression Model
Journal of Physics: Conference Series, 2020 Abstract The logistic regression model is one of the modern statistical methods developed to predict the set of quantitative variables (nominal or monotonous), and it is considered as an alternative test for the simple and multiple linear regression equation as well as it is subject to the model concepts in terms of the possibility of ...
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Stochastic Restricted Modified Mixed Logistic Estimator
Austrian Journal of StatisticsIn this study, we introduce a new estimator named the Stochastic Restricted Modified Mixed Logistic Estimator (SRMMLE), which is specifically designed to handle multicollinearity within the framework of stochastic linear restrictions.
Kayathiri Thayaparan +2 more
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The Bootstrap of the Mean for Dependent Heterogeneous Arrays [PDF]
Presently, conditions ensuring the validity of bootstrap methods for the sample mean of (possibly heterogeneous) near epoch dependent (NED) functions of mixing processes are unknown.
Halbert White, Sílvia Gonçalves
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Journal of MathematicsIn the field of chemical data modeling, it is common to encounter response variables that are constrained to the interval (0, 1). In such cases, the beta regression model is often a more suitable choice for modeling.
Solmaz Seifollahi +2 more
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AxiomsThis study introduces a new two-parameter Liu estimator (PMTPLE) for addressing the multicollinearity problem in the Poisson regression model (PRM). The estimation of the PRM is traditionally accomplished through the Poisson maximum likelihood estimator (
Mahmoud M. Abdelwahab +3 more
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Group Importance Sampling for Particle Filtering and MCMC
, 2018 Bayesian methods and their implementations by means of sophisticated Monte Carlo techniques have become very popular in signal processing over the last years.
Camps-Valls, G., Elvira, V., Martino, L.
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Special ridge-type estimator: Simulation and application to chemical data
AIP AdvancesThis study delves into regularization techniques, such as ridge regression, Liu estimator, and Kibria–Lukman estimator, as alternatives to the maximum likelihood method for addressing multicollinearity in beta regression models.
Rasha A. Farghali +4 more
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A Riemannian-Stein Kernel Method
, 2018 This paper presents a theoretical analysis of numerical integration based on interpolation with a Stein kernel. In particular, the case of integrals with respect to a posterior distribution supported on a general Riemannian manifold is considered and the
Barp, Alessandro +3 more
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