- Citations (0)
- Cited In (3)

- [Show abstract] [Hide abstract]

**ABSTRACT:**This is an eclectic tome of 100 papers in various fields of sciences, alphabetically listed, such as: astronomy, biology, calculus, chemistry, computer programming codification, economics and business and politics, education and administration, game theory, geometry, graph theory, information fusion, neutrosophic logic and set, non-Euclidean geometry, number theory, paradoxes, philosophy of science, psychology, quantum physics, scientific research methods, and statistics – containing 800 pages. It was my preoccupation and collaboration as author, co-author, translator, or co-translator, and editor with many scientists from around the world for long time. Many ideas from this book are to be developed and expanded in future explorations.01/2010; - [Show abstract] [Hide abstract]

**ABSTRACT:**The objective of the present paper is to propose a family of separate-type estimators of population mean in stratified random sampling in presence of non-response based on the family of estimators proposed by Khoshnevisan et al. (2007). Under simple random sampling without replacement (SRSWOR) the expressions of bias and mean square error (MSE) up to the first order of approximation are derived. The comparative study of the family with respect to usual estimator has been discussed. The expressions for optimum sample sizes of the strata in respect to cost of the survey have also been derived. An empirical study is carried out to shoe the properties of the estimators.09/2002; - [Show abstract] [Hide abstract]

**ABSTRACT:**In this article we have considered the problem of estimating the population mean in the stratified random sampling using the information of an auxiliary variable x which is correlated with y and suggested improved exponential ratio estimators in the stratified random sampling. The mean square error (MSE) equations for the proposed estimators have been derived and it is shown that the proposed estimators under optimum condition performs better than estimators suggested by Singh et al. (2008). Theoretical and empirical findings are encouraging and support the soundness of the proposed estimators for mean estimation.Pakistan Journal of Statistics and Operation Research. 01/2010;

Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.