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A mathematical model is a mathematical connection that describes some real-life scenario. To handle real-world problems securely and effectively, simulation modelling is required. In this article, the author investigates the stochastic regression model scenario in which the dependent and independent variables in a linear regression model follow a distribution. We assume that the dependent and independent variables both exhibit Type I Extreme Value Distribution. The estimators are then derived using the Modified Maximum Likelihood (MML) estimation method. In accordance with this, a hypothesis testing technique is developed. [ABSTRACT FROM AUTHOR]

Crime is an unavoidable social phenomenon prevailing more or less in every social structure. The incidences of crime either can be minimized or controlled, however, it is difficult to eradicate it completely. To observe crime pattern of a particular place, trend analysis plays vital role in examining shape and structure of the data. In crime study, it provides help in solving issues like crime mapping, policy-prescription, prediction, etc. Trend analysis in crime data provides comprehensive as well as extensive observations of the statistics, because of which behavioral study of the same becomes trouble-free. In this paper, an attempt has been made to analyze crime data of India for last two decades. To study the trend, Dynamic Time Warping (DTW) technique has been exercised. Hierarchical clustering of all the states and UTs has been performed as well based on crime rates to figure out places with similar pattern. Moreover, simple statistical analysis has also been carried out for better understanding of the scenario. [ABSTRACT FROM AUTHOR]

Personal network characteristics have an important role in assessing the hard-to-reach population. The purpose of the study was to assess the network characteristic, recruitment pattern and the association between personal networks with other cofactors of female sex workers (FSWs) in Nagaland, India. Four hundred and seventeen FSWs were recruited through Respondent Driven Sampling in Dimapur, Nagaland using seven seeds. Transition probability matrices and homophily indices were used to describe the network characteristics and network pattern of FSWs. Respondent Driven Sampling weighted logistic regression model was performed to observed the association. Mean personal network size of FSWs was 6.8. Heterophily was present for age at first sexual debut, duration of sex work, client volume per weeks, and personal network size. Being >30 years of age, having ≥10 years of engagement in sex work, being hotel/lodge entertainer, having more client were found significantly associated with an increased likelihood of personal network size. Higher personal network size was also found significantly associated with ever illicit drug used practices. The personal network sized and the existence of the affiliation between recruiters and recruitees may help to spread peer-driven intervention among FSWs in the region. Further, research is required on the social networks of FSWs for a better understanding of their personal network, network pattern, and high-risk behaviors in all aspects to build a better foundation for behavioral intervention. [ABSTRACT FROM AUTHOR]

Frailty model in survival analysis is a special kind of random effect model, which can also deal with heterogeneity, caused by unmeasured covariates, where the random effect (the frailty) has a multiplicative effect on the baseline hazard function. With recent advances in computing technology, Bayesian approaches to frailty models are now computationally feasible and several researchers have been developing Bayesian methodologies to analyse survival data with different frailty models. In this paper, an attempt has been made to develop two new multivariate Accelerated Failure Time Frailty models under Bayesian approach with different baseline hazard functions. For making a comparative analysis, we consider the same two Accelerated Failure Time (AFT) models without the frailty term. To illustrate the models a real life survival data set of Diabetic Retinopathy Study is used and posterior inferences are drawn using Markov Chain Monte Carlo (MCMC) simulation methods and model comparison tools like deviance information criteria (DIC) and the log pseudo marginal likelihood (LPML) are also calculated and to check the fit of the model Cox-Snell residual plot is employed. [ABSTRACT FROM AUTHOR]

Regression models form the core of the discipline of econometrics. One of the basic assumptions of classical linear regression model is that the values of the explanatory variables are fixed in repeated sampling. However, in most of the real life cases, particularly in economics the assumption of fixed regressors is not always tenable. Under a non-experimental or uncontrolled environment, the dependent variable is often under the influence of explanatory variables that are stochastic in nature. There is a huge literature related to stochastic regressors in various aspects. In this paper, a historical perspective on some of the works related to stochastic regressor is being tried to pen down based on literature search. [ABSTRACT FROM AUTHOR]

In this paper, an attempt has been made to study the performance of Cricket Players using Factor Analysis technique. For this , the dataset of 85 batsmen, 85 bowlers; and 95 batsmen, 95 bowlers have been considered from IPL9, 2016 (20 overs) and ICC World Cup, 2015 (50 overs) respectively, and the findings of this study reveals that batting capability dominates over bowling capability which is in conformity with an earlier study on same kind of game. [ABSTRACT FROM AUTHOR]

This article attempts to estimate timeliness of vaccination coverage and to model the pattern of timeliness of vaccination using techniques of survival analysis in order to trace the determinants of age-appropriate immunization status of children. Multistage cluster sampling has been used to collect information on immunization and other related variables using a pre-tested questionnaire from the universe of children of age between 12 and 36 months of two districts of Assam, India. At first, the Kaplan–Meier product limit estimator has been applied to estimate the age-appropriate immunization coverage. Though the immunization coverage as a whole is quite satisfactory in the study area, the Kaplan–Meier estimator shows poor age-appropriate immunization coverage which necessitates studying the impact of different demographic and socio-economic factors on this problem. In this context, the Cox proportional hazard model has been used which is found to be a good fit. The findings of this model show that education of mother, caste, religion and socio-economic status of the family have significant impact on the age-appropriate immunization coverage of children. Thus, it can be concluded that though the child immunization coverage in Assam has been inclining, there is still a lot of concern over the timeliness of vaccination coverage. [ABSTRACT FROM AUTHOR]

This article studies the situation of health awareness among the inhabitants of Chars (river islands) of Nalbari, Borpeta and Jorhat districts of Assam. The health awareness is measured by health expenditure. The findings reveal that all the variables—caste-residence compound status, educational attainment, economic consideration of the family, family structure and primary occupation of the families have desirable impact on health awareness. In particular, the inhabitants of Char areas of Nalbari and Borpeta districts are seen to be least health aware. Thus on the basis of the findings of this study, it can be stated that in spite of launching several schemes for the upliftment of Chars (like forming Char area development authority, forming a separate state ministry for Char development, and so forth), the people living in these Chars are still far more backward than the people living in other parts of Assam. [ABSTRACT FROM PUBLISHER]