Yayıncı "Taylor & Francis Ltd" İstatistik Bölümü Koleksiyonu için listeleme
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Comparison of partial least squares with other prediction methods via generated data
(Taylor & Francis Ltd, 2020)The purpose of this study is to compare the Partial Least Squares (PLS), Ridge Regression (RR) and Principal Components Regression (PCR) methods, used to fit regressors with severe multicollinearity against a dependent ... -
Estimation of semiparametric regression model with right-censored high-dimensional data
(Taylor & Francis Ltd, 2019)In this paper, we consider the estimation problem for the semiparametric regression model with censored data in which the number of explanatory variables p in the linear part is much larger than sample size n, often denoted ... -
Modified estimators in semiparametric regression models with right-censored data
(Taylor & Francis Ltd, 2018)In this work we introduce different modified estimators for the vector parameter and an unknown regression function g in semiparametric regression models when censored response observations are replaced with synthetic data ... -
A new robust ridge parameter estimator based on search method for linear regression model
(Taylor & Francis Ltd, 2020)A large and wide variety of ridge parameter estimators proposed for linear regression models exist in the literature. Actually proposing new ridge parameter estimator lately proving its efficiency on few cases seems endless. ... -
Path analysis and determining the distribution of indirect effects via simulation
(Taylor & Francis Ltd, 2017)The difference between a path analysis and the other multivariate analyses is that the path analysis has the ability to compute the indirect effects apart from the direct effects. The aim of this study is to investigate ...