Abstract:
This paper develops a model of the electoral process for analyzing the voters’ choice faced with two parties. A typical voter is concerned with both local governance issues and macro issues. The relative importance attached by a voter to local and macro concerns is governed by the level of education of the voter. The voter must exercise his choice based on two sets of information—the first pertains to the candidate’s efficiency level and the other pertains to the efficiency of the party as a whole. The model focuses on the case where the party with the better image has been forced to put up a less efficient candidate, as this is sufficient to analyse the trade-off involved. The model shows how the election out-comes may be influenced by the education level of the electorate and the design of election campaigns. This has implications for the design of education policy in the long run and measuring social efficiency of education.

Abstract:
The objective of this paper is to study the characteristics (geometric and otherwise) of very large attribute based undirected networks. Real-world networks are often very large and fast evolving. Their analysis and understanding present a great challenge. An Attribute based network is a graph in which the edges depend on certain properties of the vertices on which they are incident. In context of a social network, the existence of links between two individuals may depend on certain attributes of the two of them. We use the Lovasz type sampling strategy of observing a certain random process on a graph locally , i.e., in the neighborhood of a node, and deriving information about global properties of the graph. The corresponding adjacency matrix is our primary object of interest. We study the efficiency of recently proposed sampling strategies, modified to our set up, to estimate the degree distribution, centrality measures, planarity etc. The limiting distributions are derived using recently developed probabilistic techniques for random matrices and hence we devise relevant test statistics and confidence intervals for different parameters / hypotheses of interest. We hope that our work will be useful for social and computer scientists for designing sampling strategies and computational algorithms appropriate to their respective domains of inquiry. Extensive simulations studies are done to empirically verify the probabilistic statements made in the paper.

Abstract:
Motivated by various applications, we consider the problem of homogeneous human population size (N) estimation from Dual-record system (DRS) (equivalently, two-sample capture-recapture experiment). The likelihood estimate from the independent capture-recapture model Mt is widely used in this context though appropriateness of the behavioral dependence model Mtb is unanimously acknowledged. Our primary aim is to investigate the use of several relevant pseudo-likelihood methods profiling N, explicitly for model Mtb. An adjustment over profile likelihood is proposed. Simulation studies are carried out to evaluate the performance of the proposed method compared with Bayes estimate suggested for general capture-recapture experiment by Lee et al. (Statistica Sinica, 2003, vol. 13). We also analyse the effect of possible model mis-specification, due to the use of model Mt, in terms of efficiency and robustness. Finally two real life examples with different characteristics are presented for illustration of the methodologies discussed.

Abstract:
For Dual-record system, in the context of human population, the popular Chandrasekar-Deming model incorporates only the time variation effect on capture probabilities. How-ever, in practice population may undergo behavioral change after being captured first time. In this paper we focus on the Dual-record system model (equivalent to capture- recapture model with two sampling occasions) with both the time as well as behavioral response variation. The relevant model suffers from identifiability problem. Two approaches are proposed from which approximate Bayes estimates can be obtained using very simple Gibbs sampling strategies. We explore the features of our two proposed methods and their usages depending on the availability (or non-availability) of the information on the nature of behavioral response effect. Extensive simulation studies are carried out to evaluate their performances and compare with few available approaches. Finally, a real data application is provided to the model and the methods.

Abstract:
Dual-record system (DRS) (equivalently two sample Capture-recapture experiment) model with time and behavioral response variation, has attracted much attention specifically in the domain of Official Statistics and Epidemiology. The relevant model suffers from parameter identifiability problem and proper Bayesian methodologies could be helpful to overcome the situation. In this article, we have formulated the population size estimation problem in DRS as a missing data analysis under both the known and unknown directional nature of underlying behavioral response effect. Two simple empirical Bayes approaches are proposed and investigated their performances for this complex model along with a fully Bayes treatment. Extensive simulation studies are carried out to compare the performances of these competitive approaches and a real data example is also illustrated. Finally, some features of these methods and recommendations to implement them in practice are explored depending upon the availability of knowledge on the nature of behavioral response effect.

Abstract:
In many countries information on expectations collected through consumer confidence surveys are used in macroeconomic policy formulation. Unfortunately, before doing so, the consistency of responses is often not taken into account, leading to biases creeping in and affecting the reliability of the indices hence created. This paper describes how latent class analysis may be used to check the consistency of responses and ensure a parsimonious questionnaire. In particular, we examine how temporal changes may be incorporated into the model. Our methodology is illustrated using three rounds of Consumer Confidence Survey (CCS) conducted by Reserve Bank of India (RBI).

Abstract:
Let $D$ be a smoothly bounded pseudoconvex domain in $\mathbf C^n$, $n > 1$. Using the Robin function $\La(p)$ that arises from the Green function $G(z, p)$ for $D$ with pole at $p \in D$ associated with the standard sum-of-squares Laplacian, N. Levenberg and H. Yamaguchi had constructed a K\"{a}hler metric (the so-called $\La$-metric) on $D$. Assume that $D$ is strongly pseudoconvex and $ds^2$ denotes the $\La$-metric on $D$. In this article, first we prove that the holomorphic sectional curvature of $ds^2$ along normal directions converges to a negative constant near the boundary of $D$. Then, we prove that if $D$ is not simply connected, then any nontrivial homotopy class of $\pi_1(D)$ contains a closed geodesic for $ds^2$. Finally, we prove that the diminesion of the space of square integrable harmonic $(p, q)$-forms on $D$ relative to $ds^2$ is zero except when $p+q=n$ in which case it is infinite.

Abstract:
Let $D$ be a smoothly bounded pseudoconvex domain in $\mathbf C^n$, $n > 1$. Using the Robin function $\Lambda(p)$ that arises from the Green function $G(z, p)$ for $D$ with pole at $p \in D$ associated with the standard sum-of-squares Laplacian, N. Levenberg and H. Yamaguchi had constructed a K\"{a}hler metric (the so-called $\Lambda$-metric) on $D$. In this article, we study the existence of geodesic spirals for this metric.