M
Mohammad Arashi
Researcher at Ferdowsi University of Mashhad
Publications - 196
Citations - 1339
Mohammad Arashi is an academic researcher from Ferdowsi University of Mashhad. The author has contributed to research in topics: Estimator & Shrinkage estimator. The author has an hindex of 17, co-authored 177 publications receiving 1021 citations. Previous affiliations of Mohammad Arashi include Mashhad University of Medical Sciences & University of Southern Queensland.
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Feasible ridge estimator in partially linear models
Mahdi Roozbeh,Mohammad Arashi +1 more
TL;DR: In a partial linear model, some non-stochastic linear restrictions are imposed under a multicollinearity setting andSemiparametric ridge and non-ridge type estimators, in a restricted manifold are defined.
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Improved preliminary test and Stein-rule Liu estimators for the ill-conditioned elliptical linear regression model
TL;DR: The performance of the proposed Liu type estimators is compared based on the quadratic bias and risk functions under both null and alternative hypotheses, which specify certain restrictions on the regression parameters.
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Stock price forecasting for companies listed on Tehran stock exchange using multivariate adaptive regression splines model and semi-parametric splines technique
TL;DR: In this article, the authors used multivariate adaptive regression splines (MARS) model and semi-parametric splines technique for predicting stock price in this study, which is an adaptive method for regression and it fits for problems with high dimensions and several variables.
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Generalized Cross-Validation for Simultaneous Optimization of Tuning Parameters in Ridge Regression
TL;DR: In this paper, the generalized cross-validation (GCV) criterion was used to evaluate the performance of the shrinkage ridge rank regression estimator under uncertain prior information (UPI) about regression coefficients.
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On the Construction of Preliminary Test Estimator Based on Record Values for the Burr XII Model
TL;DR: In this article, the authors proposed different kinds of estimators based on the Burr type XII model, including uniformly minimum variance unbiased (UMVU) and Bayes estimators.