Estimation of population mean in successive sampling under super-population model in presence of random non response situations

The present work is an attempt to estimate the population mean on the current occasion in two-occasion successive (rotation) sampling in presence of random non response situations. The estimation strategy has been constructed under a super-population model design approach with the help of imputation technique. The estimators proposed on the current occasion cover the cases of occurrences random non responses on either of the occasions. Detail behaviors of the proposed class of estimators have been studied and its performance has been examined with the sample mean estimator. The results are demonstrated through empirical studies which establish the effectiveness of the proposed class of estimators. Suitable recommendations have been put forward to the survey statisticians for its practical application.     

Broadband Network Management and the Net Neutrality Debate

The debate of net neutrality and the potential regulation of net neutrality may fundamentally change the dynamics of data consumption and transmission through the Internet. The existing literature on economics of net neutrality focuses only on the supply side of the market, that is, a broadband service provider (BSP) may charge content providers for priority delivery of their content to consumers. In this article, we explore a complete spectrum of broadband network management options based on both the supply and demand sides of the market. We find that although the BSP always prefers the non‐neutral network management options, it does not always discriminate both sides of the market. From the social planner's perspective, we find that some network management options maximize the social welfare under certain market conditions while other options reduce the social welfare. Using the terminology from a recent Federal Communications Commission report and order, we categorize the social welfare maximizing options as “reasonable network management” and the social welfare reducing options as “unreasonable discrimination.” We also identify conditions under which the BSP's network management choices deviate from the social optimum. These conditions help establish the criteria under which the social planner might wish to regulate the BSP's actions.     

Reference distributions and inequality measurement

We investigate a general problem of comparing pairs of distributions which includes approaches to inequality measurement, the evaluation of “unfair” income inequality, evaluation of inequality relative to norm incomes, and goodness of fit. We show how to represent the generic problem simply using (1) a class of divergence measures derived from a parsimonious set of axioms and (2) alternative types of “reference distributions.” The problems of appropriate statistical implementation are discussed and empirical illustrations of the technique are provided using a variety of reference distributions.     

On Multi-Treatment Adaptive Allocation Design for Dichotomous Response

The use of ridit, as a probability score, is a very common practice to compare discrete random variables in discrete data analysis. In the present work we formulate ridit reliability functionals for some comparison of K independent binary random variables. We use such functionals to provide a generalized response-adaptive design (GRAD) on K(≥ +2) treatment-arms for dichotomous response variables. We exhibit some properties of the proposed design and compare it with some of the existing competitors by computing its various performance measures. We also provide a discussion towards a possible modification of the GRAD in the presence of covariates.     

Rational Choice and von Neumann– Morgenstern’s Stable Set: The Case of Path-dependent Procedures

Describing a procedure in which choice proceeds in a sequence, we propose two alternative ways of resolving the decision problem whenever the outcome is sequence sensitive. One way yields a rationalizable choice set, and the other way produces a weakly rationalizable choice set that is equivalent to von Neumann–Morgenstern’s stable set. It is shown that for quasi-transitive rationalization, the maximal set must coincide with its stable set.     

CLASSIFICATION, DISTRIBUTIONS AND ADMISSIBILITY IN AUTOREGRESSIVE PROCESS

The problem considered here is to classify a unit into one of two populations based on a vector of measurements on the unit. The observation vector is assumed to follow an auto-regressive process. Samples from the process are used to construct classification rules. The distributions of some classification statistics are obtained. The admissibility of some classification rules is established.     

Two population classification in Gaussian process

The problem is to classify an individual into one of two populations based on an observation on the individual which follows a stationary Gaussian process and the populations are two distinct time points. Plug-in likelihood ratio rules are considered using samples from the process. The distribution of associated classification statistics are derived. For the special case when the mis-classification probabilities are equal, the nature of dependence between the population distributions on the probability of correct classification is studied. Lower bounds and iterative method of evaluation of the optimal correlation between the populations are obtained.     

A new response-adaptive design for continuous treatment responses for phase III clinical trials

A new response-adaptive design, applicable for general class of continuous response distributions, is proposed. The allocation design is studied both theoretically and numerically and compared with some existing procedures. The applicability of the proposed procedure is also illustrated using real life data sets.     

Testing equality of survival distributions when the population marks are missing

This paper introduces a nonparametric approach for testing the equality of two or more survival distributions based on right censored failure times with missing population marks for the censored observations. The standard log-rank test is not applicable here because the population membership information is not available for the right censored individuals. We propose to use the imputed population marks for the censored observations leading to fractional at-risk sets that can be used in a two sample censored data log-rank test. We demonstrate with a simple example that there could be a gain in power by imputing population marks (the proposed method) for the right censored individuals compared to simply removing them (which also would maintain the right size). Performance of the imputed log-rank tests obtained this way is studied through simulation. We also obtain an asymptotic linear representation of our test statistic. Our testing methodology is illustrated using a real data set.