Wives’ contribution to executive growth

The corporate views on wives roles and their subsequent involvement in their husbands career seem to be quiet surprising .Even though the corporate magnates are aware of wives influence on husbands professional advancements they seldom give credit to this factor. Again it may be an eye opener for the corporations which hardly take note of the executives wives their likes or dislikes, their expectations or frustrations. They are to understand that man in his totality and decisions affecting his family have to be taken seriously. More over they should respect the right of the wives by understanding the exact role played by them. Thus this study is to understand the roles and contributions of executives wives to the success of their husbands in their professions. The study tries to minimize the gap between the corporations and the wives ,and also to make the wives aware of their peculiar role in the career advancement of their executive husbands.

ARMA modeling of time series based on rational approximation of spectral density function

This study is concerned with Autoregressive Moving Average (ARMA) models of time series. ARMA models form a subclass of the class of general linear models which represents stationary time series, a phenomenon encountered most often in practice by engineers, scientists and economists. It is always desirable to employ models which use parameters parsimoniously. Parsimony will be achieved by ARMA models because it has only finite number of parameters. Even though the discussion is primarily concerned with stationary time series, later we will take up the case of homogeneous non stationary time series which can be transformed to stationary time series. Time series models, obtained with the help of the present and past data is used for forecasting future values. Physical science as well as social science take benefits of forecasting models. The role of forecasting cuts across all fields of management-—finance, marketing, production, business economics, as also in signal process, communication engineering, chemical processes, electronics etc. This high applicability of time series is the motivation to this study.

Characterizations of Life Distributions Using Conditional Expectations of Doubly (Interval) Truncated Random Variables

In this article, we study reliability measures such as geometric vitality function and conditional Shannon’s measures of uncertainty proposed by Ebrahimi (1996) and Sankaran and Gupta (1999), respectively, for the doubly (interval) truncated random variables. In survival analysis and reliability engineering, these measures play a significant role in studying the various characteristics of a system/component when it fails between two time points. The interrelationships among these uncertainty measures for various distributions are derived and proved characterization theorems arising out of them