TRANSMUTED HALFNORMAL DISTRIBUTION: PROPERTIES AND APPLICATION

In this research, we generalize the Half normal distribution which is a special case of folded normal and truncated normal distributions. We provide a comprehensive description of the statistical properties of the subject distribution along with its reliability behavior. The usefulness of the transmuted Half normal distribution for modelling reliability data is illustrated. Keywords: Half normal Distribution, Hazard Rate function, Reliability function, Order Statistics and Parameter EstimationDOI: 10.7176/MTM/9-1-0

Simplified Methods of fitting the truncated Negative Binomial Distribution: A model that allows for Non users

Retailers monitor customer buying-behaviour as a measure of their stores’ success. However, summary measures such as the total buying-behaviour provides little insight about individual-level shopping behaviour. Additionally, behaviour may evolve over time, especially in a changing environment like the Internet. This research developed a useful stochastic model for analysing period to period fluctuations in sales thereby generalizing the model proposed by Goodhardt and Ehrenberg to allow for nonbuyers of the product category. So as the composition of the customer population changes (e.g., as customers mature or as large numbers of new and inexperienced Internet shoppers enter the market), the overall degree of buyer heterogeneity that each store faces may change. A systematic bias in their simple negative binomial distribution [NBD] model is demonstrated. If the proportion of nonbuyers is large, the simple model will be wrong. As a result, frequent buyers often comprise the preferred target segment. We find evidence supporting the fact that people who visit a store more frequently are more likely to buy. We also gives explicit formula and directions that allow a moderately analyst to perform his own conditional trend analysis. KEYWORDS:  Buying Behaviour, Negative Binomial Distribution,  Heterogeneity, Conditional Trend Analysis

Survey Error: It’s Implication on Research and Possible Remedies

This paper identifies and describes the primary sources of survey error in mail surveys and some methods typically used to assess and quantify some of these sources of error. Four sources of survey error- sampling error, non coverage error, non-response error and measurement error were discussed. Descriptions of how each of these sources of error occurs in mail surveys are provided. The paper summarizes ways of reducing these errors, if they cannot be totally avoided. Keyword: survey error, sampling error, non-coverage error, non-response error, measurement error, true score model

Consumer Purchase Behaviour in a Frequently bought product Category: Investigation and measure of Brand loyalty.

Past research has predominantly relied on models without incorporating heterogeneity as part of their methodological tools. This research investigates different ways of modeling brand loyalty using a competing risk model that incorporate brand loyalty and study its time dependence. We introduce previous models by including switch-specific hazard functions, repeat purchases, marketing mix Variables, unobserved heterogeneity and mover- stage type loyalty. An empirical example based on household purchases of disposable products is provided to illustrate the modeling approach. Results indicate that ignoring heterogeneity will lead to biased inferences concerning time dependence of brand loyalty. Keywords: Heterogeneity, Mover-Stayer loyalty, Hazard function, and Marketing mi