Murat Erişoğlu
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View article: Liu Estimator in the Multinomial Logistic Regression Model
Liu Estimator in the Multinomial Logistic Regression Model Open
This paper considers the Liu estimator in the multinomial logistic regression model. We propose some different estimators of the biasing parameter. The mean square error (MSE) is considered as the performance criterion. In order to compare…
View article: L-Moments Estimations for Mixture of Weibull Distributions
L-Moments Estimations for Mixture of Weibull Distributions Open
Mixture of Weibull distributions has wide application in modeling of heterogeneous data sets. The parameter estimation is one of the most important problems related to mixture of Weibull distributions. In this paper, we propose a L-moment …
View article: Influence Diagnostics in Two-Parameter Ridge Regression
Influence Diagnostics in Two-Parameter Ridge Regression Open
Identifying influential observations is an important part of the model building process in linear regression. There are numerous diagnostic measures based on different approaches in linear regression analysis. However, the problem of multi…
View article: Increasing the Efficiency of Percentile Parameter Estimation Method for Weibull Distribution
Increasing the Efficiency of Percentile Parameter Estimation Method for Weibull Distribution Open
The Weibull distribution is one of the most widely used probability distributions in statistical applications. The percentile parameter estimation method is commonly used in parameter estimation of the two-parameter Weibull distribution in…
View article: Empirical Type 1 Error Rate and Power Comparisons of Normality Tests with R
Empirical Type 1 Error Rate and Power Comparisons of Normality Tests with R Open
Normality is one of the main presuppositions in statistical tests. The multiplicity of the normality tests bring out another problem of choosing the appropriate test for researchers. The free software R which has a great popularity in the …
View article: An Approach for Determining the Number of Clusters in a Model-Based Cluster Analysis
An Approach for Determining the Number of Clusters in a Model-Based Cluster Analysis Open
To determine the number of clusters in the clustering analysis that has a broad range of applied sciences, such as physics, chemistry, biology, engineering, economics etc., many methods have been proposed in the literature. The aim of this…
View article: A Comparison of Information Criteria in Clustering Based on Mixture of Multivariate Normal Distributions
A Comparison of Information Criteria in Clustering Based on Mixture of Multivariate Normal Distributions Open
Clustering analysis based on a mixture of multivariate normal distributions is commonly used in the clustering of multidimensional data sets. Model selection is one of the most important problems in mixture cluster analysis based on the mi…