A novel approach based on multiple correspondence analysis for monitoring social networks with categorical attributed data

In in most cases, the distribution of communications is unknown and one may summarize social network communications with categorical attributes in a contingency table. Due to the categorical nature of the data and a large number of features, there are many parameters to be considered and estimated in the model. Hence, the accuracy of estimators decreases. To overcome the problem of high dimensionality and unknown communications distribution, multiple correspondence analysis is used to reduce the number of parameters. Then the rescaled data are studied in a Dirichlet model in which the parameters should be estimated. Moreover, two control charts, Hotelling’s T² and multivariate exponentially weighted moving average (MEWMA), are developed to monitor the parameters of the Dirichlet distribution. The performance of the proposed method is evaluated through simulation studies in terms of average run length criterion. Finally, the proposed method is applied to a real case.     

An effective discrete dynamic convexized method for solving the winner determination problem

The winner determination problem (WDP) arises in combinatorial auctions. It is known to be NP-hard. In this paper, we propose a discrete dynamic convexized method for solving this problem. We first propose an adaptive penalty function to convert the WDP into an equivalent unconstrained integer programming problem. Based on the structure of the WDP, we construct an unconstrained auxiliary function, which is maximized iteratively using a local search and is updated whenever a better maximizer is found. By increasing the value of a parameter in the auxiliary function, the maximization of the auxiliary function can escape from previously converged local maximizers. To evaluate the performance of the dynamic convexized method, extensive experiments were carried out on realistic test sets from the literature. Computational results and comparisons show that the proposed algorithm improved the best known solutions on a number of benchmark instances.     

Public sector delivery of waste management services: cases from the Indian Sub-Continent

This paper discusses the role of public sector institutions in the delivery of urban services, with a particular focus on waste management in the Indian Sub-Continent. Public sector institutions are the major stakeholders in the delivery of urban sevices. They hold the major responsibilities, funds and employ a large number of staff. The public sector institutions are also exposed to political influence and the institutional changes are often politically or donors driven. However, since new institutions such as non-government organisations and private sector are taking important roles in the actual delivery of services, there is a greater need to understand the existing linkages to promote integration. The informal sector also provides services to a large number of population. In order to promote efficient and effective delivery of urban services, it is important to work on the integrated approaches involving key stakeholders.     

A part of,yet apart from the team: Substantive membership and belonging of trans and nonbinary athletes

Increasingly, bills and policies prohibit the participation of trans women in competitive sport. The current sociopolitical moment begs the following question: how do interpersonal interactional moments function alongside formal policies and rules to shape trans athletes’ experiences of belonging in sport? Although formal institutional rules govern trans athletes’ ability to compete in sport, informal social sanctioning also denies these athletes equitable, or even de facto, membership in sport. I draw upon two case studies to explore trans athletes’ experiences of membership in elite “women's” sport. I apply Evelyn Nakano Glenn's work on citizenship to consider how trans athletes’ experiences of belonging are influenced by both formal rules imposed by organizations as well as informal social interactions with members of their sporting communities. Inclusion is not synonymous with membership. Trans athletes render visible the ways in which this system functions to contain the diversity of humanity's gender expression.     

Distribution of product and quotient of bivariate generalized exponential distribution

In this work we derive closed form expressions for the probability density functions and moments of the quotient and product of the components of the bivariate generalized exponential distribution introduced by Kundu and Gupta (J Multivariate Anal, 100:581–593, 2009) and compute the percentage points. The derivations will be useful for practitioners of this bivariate model. We then give a real data application of the product.     

Does inflation targeting lower inflation and spur growth?

Over the last few decades several countries have turned to inflation targeting as a policy choice for instilling stability into their economies. Prior studies have shown that inflation targeting has reduced inflation in those countries without significantly impacting GDP. This study seeks to improve upon these results by identifying the impact of timing on the policy decision as well as its impact as related to specific regions of the world. The focus is on developing countries across six regions. We find significant regional variation in developing countries in our sample in terms of the direction of changes in inflation following a switch to the inflation targeting policy. Moreover, although the impact of inflation targeting on real GDP is minimal overall, there is a statistically significant increase in real GDP among developing countries in certain regions only, namely, Europe, Latin America, and the Middle East.     

On the generalized process capability under simple and mixture models

Process capability (PC) indices measure the ability of a process of interest to meet the desired specifications under certain restrictions. There are a variety of capability indices available in literature for different interest variables such as weights, lengths, thickness, and the life time of items among many others. The goal of this article is to study the generalized capability indices from the Bayesian view point under different symmetric and asymmetric loss functions for the simple and mixture of generalized lifetime models. For our study purposes, we have covered a simple and two component mixture of Maxwell distribution as a special case of the generalized class of models. A comparative discussion of the PC with the mixture models under Laplace and inverse Rayleigh are also included. Bayesian point estimation of maintenance performance of the system is also part of the study (considering the Maxwell failure lifetime model and the repair time model). A real-life example is also included to illustrate the procedural details of the proposed method.     

序言

编者按:由埃及著名学者侯赛因·卡米勒·巴哈丁著,朱威烈、丁俊译的<十字路口>一书已由上海外语教育出版社于2005年4月出版,特选录其中的"序言"、"译后记"及部分章节,以飨读者.     

Testing the equality of quantiles for several normal populations

Many procedures exist for testing equality of means or medians to compare several independent distributions. However, the mean or median do not determine the entire distribution. In this article, we propose a new small-sample modification of the likelihood ratio test for testing the equality of the quantiles of several normal distributions. The merits of the proposed test are numerically compared with the existing tests—a generalized p-value method and likelihood ratio test—with respect to their sizes and powers. The simulation results demonstrate that proposed method is satisfactory; its actual size is very close to the nominal level. We illustrate these approaches using two real examples.     

The Bayesian elastic net regression

A Bayesian elastic net approach is presented for variable selection and coefficient estimation in linear regression models. A simple Gibbs sampling algorithm was developed for posterior inference using a location-scale mixture representation of the Bayesian elastic net prior for the regression coefficients. The penalty parameters are chosen through an empirical method that maximizes the data marginal likelihood. Both simulated and real data examples show that the proposed method performs well in comparison to the other approaches.