A multimodal skewed extension of normal distribution: its properties and applications

A multimodal skewed extension of normal distribution is proposed by applying the general method as in [Huang WJ, Chen YH. Generalized skew-Cauchy distribution. Stat Probab Lett. 2007;77:1137–1147] for the construction of skew-symmetric distributions by using a trigonometric periodic skew function. Some of its distributional properties are investigated. Properties of maximum likelihood estimation of the parameters are studied numerically by simulation. The suitability of the proposed distribution in empirical data modelling is investigated by carrying out comparative fitting of two real-life data sets.     

Crisis communication in higher education: The use of “negotiation” as a strategy to manage crisis

This case study examined the crisis response strategies of Louisiana State University after its women's head basketball coach resigned amid charges of inappropriate conduct with former basketball players. This case study draws on relationship management and negotiation as the theoretical lens to examine the efforts of the University in managing relationships and restoring its image. Data for this study was collected through opened-ended questionnaires from students, faculty, and staff at the University. The findings from this study indicate that the good reputation of the University was responsible for the positive evaluation of the crisis management. In addition, results from this study suggest that “negotiation” can play an important role in managing a crisis when the conflicting parties are not willing to participate in a dialogue.     

Alternating sums of sub-diagonal product moments of order statistics

A relation satisfied by the product moments of order statistics from an arbitrary continuous distribution symmetric about the origin has been established in this paper. We have shown that in such a situation, for samples of even size, sum of the sub-diagonal product moments of order statistics with alternating plus and minus signs assumes a compact form.     

Urbanization of Muslim Community in India—A Metaphor for Development? Evidences from States of West Bengal and Kerala

Historically, the religious affiliation of urbanization in India has always rendered a relative advantage for Muslim Community. During 2000–2011, in situ urbanization process has strengthened this popular belief. This trend is more pronounced in the states of Kerala and West Bengal, perhaps due to the colossal escalation of new Census Towns (CTs). This present study is an endeavour to understand whether recent upsurge of urbanization among Muslims in India can be linked with “development” in these two states based on availabilities of Basic Urban Infrastructures (BUIs), principally in the new CTs. This has been done by employing an “availability index” of infrastructures by obtaining data from Village Directory of West Bengal and Kerala, Census of India. The BUIs include educational and health institutions, bus and railway services and drinking water facility. Most importantly, where these amenities were absent in 2001, the distance travelled by the inhabitants, to get access to these services has also been examined here. The study concludes through extending the debate on whether an increase in the number of population, particularly of Muslim community, in urban areas can be taken as a true signature of development or not.     

Assessing social vulnerability and identifying spatial hotspots of flood risk to inform socially just flood management policy

This study presents the first nationwide spatial assessment of flood risk to identify social vulnerability and flood exposure hotspots that support policies aimed at protecting high-risk populations and geographical regions of Canada. The study used a national-scale flood hazard dataset (pluvial, fluvial, and coastal) to estimate a 1-in-100-year flood exposure of all residential properties across 5721 census tracts. Residential flood exposure data were spatially integrated with a census-based multidimensional social vulnerability index (SoVI) that included demographic, racial/ethnic, and socioeconomic indicators influencing vulnerability. Using Bivariate Local Indicators of Spatial Association (BiLISA) cluster maps, the study identified geographic concentration of flood risk hotspots where high vulnerability coincided with high flood exposure. The results revealed considerable spatial variations in tract-level social vulnerability and flood exposure. Flood risk hotspots belonged to 410 census tracts, 21 census metropolitan areas, and eight provinces comprising about 1.7 million of the total population and 51% of half-a-million residential properties in Canada. Results identify populations and the geographic regions near the core and dense urban areas predominantly occupying those hotspots. Recognizing priority locations is critically important for government interventions and risk mitigation initiatives considering socio-physical aspects of vulnerability to flooding. Findings reinforce a better understanding of geographic flood-disadvantaged neighborhoods across Canada, where interventions are required to target preparedness, response, and recovery resources that foster socially just flood management strategies.     

Exploring the Urban–Rural Incarceration Divide: Drivers of Local Jail Incarceration Rates in the United States

ABSTRACT

A large body of research has focused on understanding mass incarceration in the United States through the lens of federal and state prison growth. However, local jail systems, with 11 million admissions each year, have received less research attention despite their broad impact on communities. Preliminary analysis conducted by the Vera Institute of Justice (Vera) uncovered geographical disparities in county jail incarceration rates. Contrary to assumptions that incarceration is an urban phenomenon, Vera discovered that, in recent decades, pretrial jail rates have declined or remained flat in many urban areas, whereas rates have grown in rural counties. In an effort to uncover factors contributing to continued jail growth in rural areas, Vera joined forces with Two Sigma’s Data Clinic, a volunteer-based program that leverages Two Sigma employees’ data science expertise. Determinants of local jail rates from 2000–2013 were examined using a generalized estimating equations (GEE) model to account for correlations within counties over time. Results revealed that county-level poverty, police expenditures, and spillover effects from other county and state authorities are significant predictors of local jail rates. Investigation of model residuals revealed clusters of counties where observed rates were much higher than expected conditioned upon county variables.     

Modelling of low count heavy tailed time series data consisting large number of zeros and ones

In this paper, we construct a new mixture of geometric INAR(1) process for modeling over-dispersed count time series data, in particular data consisting of large number of zeros and ones. For some real data sets, the existing INAR(1) processes do not fit well, e.g., the geometric INAR(1) process overestimates the number of zero observations and underestimates the one observations, whereas Poisson INAR(1) process underestimates the zero observations and overestimates the one observations. Furthermore, for heavy tails, the PINAR(1) process performs poorly in the tail part. The existing zero-inflated Poisson INAR(1) and compound Poisson INAR(1) processes have the same kind of limitations. In order to remove this problem of under-fitting at one point and over-fitting at others points, we add some extra probability at one in the geometric INAR(1) process and build a new mixture of geometric INAR(1) process. Surprisingly, for some real data sets, it removes the problem of under and over-fitting over all the observations up to a significant extent. We then study the stationarity and ergodicity of the proposed process. Different methods of parameter estimation, namely the Yule-Walker and the quasi-maximum likelihood estimation procedures are discussed and illustrated using some simulation experiments. Furthermore, we discuss the future prediction along with some different forecasting accuracy measures. Two real data sets are analyzed to illustrate the effective use of the proposed model.     

A New Discrete Distribution Related to Generalized Gamma Distribution and Its Properties

In this article, a new discrete distribution related to the generalized gamma distribution (Stacy, 1962) is derived from a statistical mechanical setup. This new distribution can be seen as generalization of two-parameter discrete gamma distribution (Chakraborty and Chakravarty, 2012) and encompasses discrete version of many important continuous distributions. Some basic distributional and reliability properties, parameter estimation by different methods, and their comparative performances using simulation are investigated. Two-real life data sets are considered for data modeling and likelihood ratio test for illustrating the advantages of the proposed distribution over two-parameter discrete gamma distribution.