New exact Bayesian prediction of the range for the exponential lifetime based on fixed and random sample sizes

We consider the problem of predictive interval for the range of the future observations from an exponential distribution. Two cases are considered, (1) Fixed sample size (FSS). (2) Random sample size (RSS). Further, I derive the predictive function for both FSS and RSS in closely forms. Random sample size is appeared in many application of life testing. Fixed sample size is a special case from the case of random sample size. Illustrative examples are given. Factors of the predictive distribution are given. A comparison in savings is made with the above method. To show the applications of our results, we present some simulation experiments. Finally, we apply our results to some real data sets in life testing.

Modified chain regression type estimator for population mean in the presence of non- response

<p>A modified chain regression type estimator for population mean in the presence of non-response have been proposed replacing Hansen &amp; Hurwitz (1946) estimator for population mean by Searls (1964) type improved estimator and using Hansen &amp; Hurwitz (1946) estimator for based on available information comparing to the study character in the second phase sample. The expressions for MSE for fixed sample size and also fixed cost have been obtained. The empirical studies show that the proposed estimator is more efficient than the relevant estimators in the case of fixed sample size as well as for fixed cost.</p>

Testing Models of Consumer Search Using Data on Web Browsing and Purchasing Behavior

Using a large dataset on web browsing and purchasing behavior we test to what extent consumers are searching in accordance to various search models. We find that the benchmark model of sequential search with a known price distribution can be rejected based on recall patterns found in the data as well as the absence of dependence of search decisions on prices. Our findings suggest fixed sample size search provides a more accurate description of search behavior. We then utilize the fixed sample size search model to estimate demand elasticities of online bookstores in an environment where store preferences are heterogeneous. (JEL D12, D83, L81)