1005 Submissions

[4] viXra:1005.0068 [pdf] submitted on 11 Mar 2010

Randomness and Optimal Estimation in Data Sampling

Authors: M. Khoshnevisan, S. Saxena, H. P. Singh, S. Singh, Florentin Smarandache
Comments: 63 pages.

The purpose of this book is to postulate some theories and test them numerically. Estimation is often a difficult task and it has wide application in social sciences and financial market. In order to obtain the optimum efficiency for some classes of estimators, we have devoted this book into three specialized sections.
Category: Statistics

[3] viXra:1005.0048 [pdf] submitted on 11 Mar 2010

Estimation of Mean in Presence of Non Response Using Exponential Estimator

Authors: Rajesh Singh, Mukesh Kumar, Manoj K. Chaudhary, Florentin Smarandache
Comments: 11 pages

This paper considers the problem of estimating the population mean using information on auxiliary variable in presence of non response. Exponential ratio and exponential product type estimators have been suggested and their properties are studied. An empirical study is carried out to support the theoretical results.
Category: Statistics

[2] viXra:1005.0020 [pdf] submitted on 8 May 2010

Confidence Intervals for the Pythagorean Formula in Baseball

Authors: David D. Tung
Comments: 27 Pages.

In this paper, we will investigate the problem of obtaining confidence intervals for a baseball team's Pythagorean expectation, i.e. their expected winning percentage and expected games won. We study this problem from two different perspectives. First, in the framework of regression models, we obtain confidence intervals for prediction, i.e. more formally, prediction intervals for a new observation, on the basis of historical binomial data for Major League Baseball teams from the 1901 through 2009 seasons, and apply this to the 2009 MLB regular season. We also obtain a Scheffé-type simultaneous prediction band and use it to tabulate predicted winning percentages and their prediction intervals, corresponding to a range of values for log(RS=RA). Second, parametric bootstrap simulation is introduced as a data-driven, computer-intensive approach to numerically computing confidence intervals for a team's expected winning percentage. Under the assumption that runs scored per game and runs allowed per game are random variables following independent Weibull distributions, we numerically calculate confidence intervals for the Pythagorean expectation via parametric bootstrap simulation on the basis of each team's runs scored per game and runs allowed per game from the 2009 MLB regular season. The interval estimates, from either framework, allow us to infer with better certainty as to which teams are performing above or below expectations. It is seen that the bootstrap confidence intervals appear to be better at detecting which teams are performing above or below expectations than the prediction intervals obtained in the regression framework.
Category: Statistics

[1] viXra:1005.0003 [pdf] submitted on 10 Mar 2010

N-Algebraic Structures and S-N-Algebraic Structures

Authors: W. B. Vasantha Kandasamy, Florentin Smarandache
Comments: 209 pages

In this book, for the first time we introduce the notions of Ngroups, N-semigroups, N-loops and N-groupoids. We also define a mixed N-algebraic structure. We expect the reader to be well versed in group theory and have at least basic knowledge about Smarandache groupoids, Smarandache loops, Smarandache semigroups and bialgebraic structures and Smarandache bialgebraic structures.
Category: Statistics