Open Access. Powered by Scholars. Published by Universities.®

Physical Sciences and Mathematics Commons

Open Access. Powered by Scholars. Published by Universities.®

Articles 61 - 65 of 65

Full-Text Articles in Physical Sciences and Mathematics

Separate Ratio-Type Estimators Of Population Mean In Stratified Random Sampling, Rajesh Tailor, Hilal A. Lone May 2014

Separate Ratio-Type Estimators Of Population Mean In Stratified Random Sampling, Rajesh Tailor, Hilal A. Lone

Journal of Modern Applied Statistical Methods

Separate ratio-type estimators for population mean with their properties are considered. Some separate ratio-type estimators for population mean using known parameters of auxiliary variate are proposed. The bias and mean squared error of the proposed estimators are obtained up to the first degree of approximation. It is shown that the proposed estimators are more efficient than unbiased estimators in stratified random sampling and usual separate ratio estimators under certain obtained conditions. To judge the merits of the proposed estimators, an empirical study was conducted.


Inference For The Rayleigh Distribution Based On Progressive Type-Ii Fuzzy Censored Data, Abbas Pak, Gholam Ali Parham, Mansour Saraj May 2014

Inference For The Rayleigh Distribution Based On Progressive Type-Ii Fuzzy Censored Data, Abbas Pak, Gholam Ali Parham, Mansour Saraj

Journal of Modern Applied Statistical Methods

Classical statistical analysis of the Rayleigh distribution deals with precise information. However, in real world situations, experimental performance results cannot always be recorded or measured precisely, but each observable event may only be identified with a fuzzy subset of the sample space. Therefore, the conventional procedures used for estimating the Rayleigh distribution parameter will need to be adapted to the new situation. This article discusses different estimation methods for the parameters of the Rayleigh distribution on the basis of a progressively type-II censoring scheme when the available observations are described by means of fuzzy information. They include the maximum likelihood …


On The Exponentiated Weibull Distribution For Modeling Wind Speed In South Western Nigeria, Olanrewaju I. Shittu, K A. Adepoju May 2014

On The Exponentiated Weibull Distribution For Modeling Wind Speed In South Western Nigeria, Olanrewaju I. Shittu, K A. Adepoju

Journal of Modern Applied Statistical Methods

One of the bases for assessment of wind energy potential for a specified region is the probability distribution of wind speed. Thus, appropriate and adequate specification of the probability distribution of wind speed becomes increasingly important. Several distributions have been proposed for describing wind distribution. Among the most popular distributions is the Weibull whose choice is due to its flexibility. An exponentiated Weibull distribution is proposed as an alternative to model wind speed data with a view to comparing it with the existing Weibull distribution. Results indicate that the proposed distribution outperforms the existing Weibull distribution for modeling wind speed …


Distance Correlation Coefficient: An Application With Bayesian Approach In Clinical Data Analysis, Atanu Bhattacharjee May 2014

Distance Correlation Coefficient: An Application With Bayesian Approach In Clinical Data Analysis, Atanu Bhattacharjee

Journal of Modern Applied Statistical Methods

The distance correlation coefficient – based on the product-moment approach – is one method by which to explore the relationship between variables. The Bayesian approach is a powerful tool to determine statistical inferences with credible intervals. Prior information about the relationship between BP and Serum cholesterol was applied to formulate the distance correlation between the two variables. The conjugate prior is considered to formulate the posterior estimates of the distance correlations. The illustrated method is simple and is suitable for other experimental studies.


Vol. 13, No. 1 (Full Issue), Jmasm Editors May 2014

Vol. 13, No. 1 (Full Issue), Jmasm Editors

Journal of Modern Applied Statistical Methods

No abstract provided.