A new approach using the genetic algorithm for parameter estimation in multiple linear regression with long-tailed symmetric distributed error terms: An application to the Covid-19 data.

Maximum likelihood (ML) estimators of the model parameters in multiple linear regression are obtained using genetic algorithm (GA) when the distribution of the error terms is long-tailed symmetric. We compare the efficiencies of the ML estimators obtained using GA with the corresponding ML estimators obtained using other iterative techniques via an extensive Monte Carlo simulation study. Robust confidence intervals based on modified ML estimators are used as the search space in GA.

Modified maximum likelihood estimator under the Jones and Faddy's skew -error distribution for censored regression model.

It is well-known that classical Tobit estimator of the parameters of the censored regression (CR) model is inefficient in case of non-normal error terms. In this paper, we propose to use the modified maximum likelihood (MML) estimator under the Jones and Faddy's skew -error distribution, which covers a wide range of skew and symmetric distributions, for the CR model. The MML estimators, providing an alternative to the Tobit estimator, are explicitly expressed and they are asymptotically equivalent to the maximum likelihood estimator.

Evaluation of surface water quality characteristics by using multivariate statistical techniques: a case study of the Euphrates river basin, Turkey.

The surface water quality of the Euphrates river basin in Turkey are evaluated by using the multivariate statistical techniques known as factor analysis (FA) and multidimensional scaling (MDS) analysis. When FA was applied to the water quality data obtained from the 15 different surface water quality monitoring stations, two factors were identified, which were responsible from the 86.02% of the total variance of the water quality in the Euphrates river basin.

Effects of physical environment on the stress levels of hemodialysis nurses in Ankara Turkey.

This study has been planned and executed as a field study for identifying the effect of physical environment on the stress levels of hemodialysis nurses who work in the official and private hemodialysis centers in the capital city of Turkey, Ankara (n=161). According to the results obtained from the study, it has been seen that "education level" and "institution of employment" of the hemodialysis nurses are significantly related with the stress levels of the hemodialysis nurses. Nurses' age, marital status, number of children, occupational seniority, years of working, employment status, husbands' occupation and husbands' educational levels are not significantly related with their stress levels.