12 citations · 12 across the 6 of their papers we have counts for
7 papers
Combining Empirical Likelihood and Robust Estimation Methods for Linear Regression Models
Şenay Özdemir, Olcay Arslan
Ordinary least square (OLS), maximum likelihood (ML) and robust methods are the widely used methods to estimate the parameters of a linear regression model. It is well known that t…
Robust Parameter Estimation of Regression Model with AR(p) Error Terms
Yetkin Tuaç, Yeşim Güney Birdal Şenoğlu, Olcay Arslan
In this paper, we consider a linear regression model with AR(p) error terms with the assumption that the error terms have a t distribution as a heavy tailed alternative to the norm…
Variable Selection in Restricted Linear Regression Models
Yetkin Tuaç, Olcay Arslan
The use of prior information in the linear regression is well known to provide more efficient estimators of regression coefficients. The methods of non-stochastic restricted regres…
On the Robustness and Asymptotic Properties for Maximum Likelihood Estimators of Parameters in Exponential Power and its Scale Mixture Form Distributions
Mehmet Niyazi Cankaya, Olcay Arslan
The normality assumption on data set is very restrictive approach for modelling. The generalized form of normal distribution, named as an exponential power (EP) distribution, and i…
Double Reweighted Estimators for the Parameters of the Multivariate t Distribution
Fatma Zehra Doğru, Y. Murat Bulut, Olcay Arslan
The t-distribution has many useful applications in robust statistical analysis. The parameter estimation of the t-distribution is carried out using ML estimation method, and the ML…
Finite Mixtures of Multivariate Skew Laplace Distributions
Fatma Zehra Doğru, Y. Murat Bulut, Olcay Arslan
In this paper, we propose finite mixtures of multivariate skew Laplace distributions to model both skewness and heavy-tailedness in the heterogeneous data sets. The maximum likelih…