bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bivariate Geometric Vitality Function and Some Characterization Results
Authors: Abdul-Sathar E.I. , Rajesh G. , Nair K.R. Muraleedharan 
Published: August 2016

Abtsrcat In the present work we extends the definition of geometric vitality function, considered by Nair and Rajesh (2000) to the bivariate set up. We also look into the problem of characterizing some bivariate models using the functional form of the bivariate geometric vitality function.
A Note on Approximating Continuous Distribution Functions
Authors: Habibi Reza 
Published: August 2016

Abtsrcat This paper deals with the approximation of distribution func- tions of complicated statistics using Beta distribution. The problem is motivated and the performance of our method is evaluated by several examples. Two methods are suggested to estimate the parameters of Beta distribution. We approximate distributions of cusum statistic and Hsu's G test statistic by this method. Error analysis is given. Fitting the mixture of Beta distributions are examined. Finally, a discussion Section is given.
Fundamental Planes for Galaxy Data with Measuremental Errors
Authors: Mondal Saptarshi , Warule Bharat , Chattopadhyay Tanuka 
Published: August 2016

Abtsrcat Regression planes using three variables have been derived including observed measuremental errors in all the variables. It is found that in most situations the variances of the regression coefficients are reduced by inclusion of measuremental errors. To get rid of the confusion of dependent and independent variables a symmetric regression plane is also suggested as a representative one, though the choice is never unique in case of three variables. The model is tested in case of fundamental planes (FP) for some early type galaxies.
Estimation of Median Household Income for Small Areas : A Bayesian Semiparametric Approach
Authors: Bhadra Dhiman , Ghosh Malay , Kim Dalho 
Published: August 2016

Abtsrcat Estimation of median income of small areas is one of the prin- cipal targets of inference of the U.S Bureau of Census. These estimates play an important role in the formulation of various governmental decisions and policies. Since these estimates are collected over time, they often possess an inherent longitudinal pattern. Taking proper account of this time varying pattern may result in better estimates for the current or future median house-hold incomes for a particular state or county. In this study, we put forward a semiparametric modeling procedure for estimating the median household income for all the U.S states. Our models include a nonparametric functional part for accommodating any unspecified time varying income pattern and also a state specific random effect to account for the within-state correlation of the income observations. Model fitting and parameter estimation is carried out in a hierarchical Bayesian framework using Markov chain Monte Carlo (MCMC) methodology. It is seen that the semiparametric model esti- mates can be superior to both the direct estimates and the Census Bureau estimates. Overall, our study indicates that proper modeling of the underly- ing longitudinal income profiles can improve the performance of model based estimates of household median income of small areas.
On the Foundations of Dependency Models and Parameters for Random Variables on Cylinder R3
Authors: Seal Babulal , Sengupta Ashis 
Published: August 2016

Abtsrcat Directional data often deal with observations on circles, spheres, cylinders, torus, etc. The notion of dependency between the variables involved and the development of related models and dependency parameters are of fundamental importance in this area. Here we develop a method of obtaining regression curves on manifold (cylinder) on R3 based on a differential geometric approach. With an aim to develop statistical inference procedures, we propose useful distribution on the cylinder for which the dependency parameter can be elegantly elucidated, and demonstrate how this parameter can be estimated in practice.
Empirical Bayes Prediction in Random Effects Models with Covariates Subject to Measurement Error
Authors: Guao Meixi , Ghosh Malay 
Published: August 2016

Abtsrcat The paper considers a nested error linear regression model with multiple covariates subject to measurement error. An efficient empirical Bayes (EB) predictor is obtained using the information on both the observed response variables and the observed covariates. We derive a correct second- order unbiased approximation to the mean squared error (MSE) of the EB predictor.
On Sequential Point Estimation in a Uniform Distribution with Adjusted Non-Sufficient Estimators : A Comparative Study and Real Data Illustration
Authors: Bhattacharjee Debanjan , Mukhopadhyay Nitis 
Published: August 2016

Abtsrcat The purely sequential minimum risk point estimation procedure for the unknown parameter θ (> 0) in a Uniform (0; θ) population has been discussed in this article. This is developed under a squared error loss plus a linear cost function of sampling. The unknown parameter θ is estimated by means of four different estimators in the stopping rule, where as in the loss function two different unbiased estimators of θ are proposed. The unbiased estimators are randomly stopped versions of Χ n: n and X¯ n in either loss function. Performances of such estimators are compared. Clearly, using a randomly stopped version of X¯ n would amount to some loss of in- formation when compared with a corresponding randomly stopped largest sample order statistic under both loss functions and the stopping rules. In this paper, we explore a novel approach to recover any loss of information by fine-tuning the loss function and then properly tailoring the associated sequential methodologies. We examine how the sequential risks of our newly proposed methodologies would compare with those associated with the ex- isting sequential estimators and illustrate our methodologies with the help of a real dataset.
Stability of the Characterization Results in Terms of Hazard and Reverse Hazard Rates Under Matusita Distance
Authors: Roy Dilip 
Published: August 2016

Abtsrcat The classical approach of stochastic modeling is to first guess a model and then to validate the same using observed data and some test for goodness of fit. Unfortunately, this is not a very rational approach. The initial choice of model becomes a subjective one, some goodness of fit test may demand for large number of observations and difierent models may fit well for the same data set. Given these limitations of the classical approach, one may, as an alternative, make use of characterization results. At the same time, to take care of the difficulties in verification of characterizing properties one needs stability properties as well. Stability results have been mostly studied for the exponential distribution. So far as non-exponential distributions are concerned, one may refer to only few works. The present study deals with stability properties in terms of Matusita distance for characterization results involving reliability measures. These results are generic in nature and can be used for the distribution cor- responding to any non-negative random variable.
On Generalized Quality Capability Index
Authors: Maiti Sudhansu S. , Saha Mahendra 
Published: August 2016

Abtsrcat A Generalized Process Capability Index, defined as the ratio of proportion of specification conformance (or, process yield) to proportion of desired (or, natural) conformance, has been developed by Maiti et al.(2010). Almost all the process capabilities defined in the literature are directly or indirectly associated with this generalized index. In this article, a loss function has been attached to the product quality characteristic for deviation from its target to define the index named as generalized quality capability index. Symmetric as well as asymmetric loss functions have been considered. We deal with the index in case of normal, non-normal and discrete processes. An algorithm for determining optimum process center for an off-centered process has been prescribed. A process data set has been analyzed.
The Role of Genotype and Phenotype Based Risk Factors in Patients Suffering from Acute Coronary Syndrome
Authors: Roy Puspita Das , Basu Cynthia , Das Sonali , Dasgupta Anjan Kr. , Ganguli Bhaswati 
Published: August 2016

Abtsrcat In this paper we apply statistical classification techniques to a case-control study. The data analysed relates to Acute Coronary Syndrome (ACS). We discuss an adaptation of the Naive Bayes method, and assess the results using an analysis of deviance based approach. Analysis of deviance is used to rank the driver variables, such as phenotype and genotype variables to their relative contribution to classify a new case into one of ACS or non-ACS group. Results from the case-study reveal that a combination of Single Nucleotide Polymorphism (SNP) 2 and Single Nucleotide Polymorphism 4 is the most important, and the aggregation of platelets on addition of Adenosine-di-phosphate along with nano particles the next most important factors in classifying an unseen patient into one of the two groups. Some limitations and future analyses are also discussed.
Time Series Models Using Geometric Stable Distributions
Authors: Kuttykrishnan A.P. 
Published: August 2016

Abtsrcat Geometric stable distributions received much attention in recent years and their applications in different fields ranging from reliability to financial mathematics are well established by several researchers. It can be used in modeling peaked and heavy tailed observations that may be a result of a random number of independent innovations. Although the theory and applications of geometric stable distributions are well developed and appeared in many literature in recent years, their applications in time series modeling are not developed. Present work aims at developing autoregressive model using geometric stable distributions as marginal distributions.
A Class of Distributions Defined by Quantile Density Function
Authors: Midhu N.N. , Sankaran P.G. 
Published: August 2016

Abtsrcat In the present paper, we introduce and study a class of distributions that has simple quantile density function. Various distributional properties and reliability characteristics of the class are studied. The method of L-moments is employed to estimate parameters of the proposed class of distributions. Finally, we apply the proposed class to two real data sets.
Barndorff-Nielsen's form of the Law of the Iterated Logarithm for rth Moving Maxima
Authors: Vasudeva R. , Srilakshminarayana G. 
Published: August 2016

Abtsrcat Let { Xn} be a sequence of independent identically distributed random variables, defined over a common probability space (Ω,ℱ, P) with a continuous distribution function F and let η r,n denote the r th upper order statistic among ( Xn-an+1, Xn-an+2,... Xn); n, ≥ 1, where { a n} is a non-decreasing sequence of integers such that 0 < a n ≤ n. For a large class of distributions, we obtain Barndor-Nielson's form of the law of the iterated logarithm for {η r,n}.
A two Sample Test Based on Mutual Information
Authors: Guha Apratim , Chothia Tom 
Published: August 2016

Abtsrcat For two independently drawn samples from continuous distributions, a permutation test based on the mutual information statistic is proposed for the null hypothesis that both the samples originate from the same population. It is demonstrated through simulation that this test is more powerful than the commonly used nonparametric tests in many situations. We also discuss the test in a real life setup.
Clustering Based Small Area Estimation : an Application to Meap Data
Authors: Maiti Tapabrata , Ren Hao , Dass Sarat C. , Lim Chae Young , Maier Kimberly S. 
Published: August 2016

Abtsrcat The Michigan Educational Assessment Program, known as MEAP, conducted by the state department of education, is a standardized test. The test is taken by all public school students in Michigan and the results are being used for comparing schools and school districts. Because of widely varying school districts in size, the direct use of average score could be misleading. The direct averages for small school districts are, in particular, quite unstable. This requires “smoothing” the data before they can be used. There are several smoothing procedures available in statistical literature that “borrow strength” from other areas. We choose to apply small area estimation technique to analyze 4-th grade average math score available in MEAP. The standard small area estimation methods shrunk the direct averages towards overall statewide average but it can suffer from over-shrinkage problem. To resolve over-shrinkage, a clustering based small area estimation technique has been applied to the data. This allows borrowing strength both locally and globally. In terms of mean squared error and coefficient of variation, the resultant estimates are more stable and hence are more reliable to use.
A Discrete Analogue of Reciprocal Coordinate Subtangent and its Role in Characterization Problems
Authors: Sunoj S.M. , Sreejith T.B. 
Published: August 2016

Abtsrcat The concept of reciprocal coordinate subtangent (RCST) has been used in statistical literature as a useful tool to study the monotone behaviours of a continuous density function and for characterizing probability distributions through its functional forms. Motivated by this, in the present paper, we consider a discrete analogue of RCST introduced by Gupta et al. (1997) and study its usefulness in modeling probability mass functions. Characterization results are proved for models viz. geometric, discrete Burr and modified power series. The concept is also extended to the weighted models and proves some useful results as models such as logarithmic series, residual lifetime and partial sum (renewal) distributions. Finally, a new definition for discrete analogue of RCST is introduced and examined its usefulness in modeling proportional hazard models in discrete time.
Finite Population Distribution Function Estimation Using P-Splines
Authors: Adhya Sumanta , Banerjee Tathagata , Chattopadhyay Gaurangadeb 
Published: August 2016

Abtsrcat Estimating finite population distribution function (hereafter FPDF) is an important problem to the survey samplers since it summarizes almost all the relevant information of interest about the finite population. Chambers and Dunstan (1986) (henceforth CD) in their seminal paper propose a predictive estimator of FPDF incorporating the unit level auxiliary information available for the entire population. CD estimator assumes a linear regression model in the superpopulation. However, even for moderate deviation from linearity assumption, significant performance deterioration of CD estimator is observed. Here we propose a predictive estimator of FPDF based on a semiparametric regression model. For this we use recently developed penalized splines (P-splines) regression. The proposed estimator performs better than CD estimator if the linearity assumption fails. We find its asymptotic bias and variance. Finally, we compare the performance of the proposed estimator with other alternative estimators through simulation studies and illustrate its use with a real data set.
An Alternate Way of Obtaining Gomez-Deniz form of Generalized Geometric Distribution
Authors: Sastry D.V.S. , Bhati Deepesh 
Published: August 2016

Abtsrcat In this paper we propose another approach to obtain a generalized geometric distribution. Starting with a Poisson distribution and assuming that the parameter (λ) of the Poisson distribution follows geometrically (declining) weighted exponential distribution, we obtain a generalized geometric distribution.
A Purely Sequential Estimation Procedure for the Parameter of U(θ,mθ) Distribution
Authors: Patil H.S. 
Published: August 2016

Abtsrcat In the literature, an extensive work on sequential fixed width confidence interval (CI) for the parameter of U(0, θ) model is available. In this article we propose a fixed width (1-) level sequential CI for the parameter θ of U(θ, mθ) distribution, where m > 1 is known, based on the large-sample approximation of coverage probability.
Redefining cultural, national, and religious identity: The Christian–Vodouist dialogue?
Authors: Joseph Celucien L. 
Published: August 2016

This essay examines the work of two prominent progressive Haitian Theologians: Laënnec Hurbon, a Catholic Theologian and former Priest, and Jean Fils-Aimé, a Protestant Theologian and former Pastor in Montreal, and their interaction with the Vodou religion. Both thinkers have written prolifically about the three major religious expressions in Haiti and the enduring religious conflict between Protestantism, Catholicism, and Vodou in the Caribbean nation. The history of relations between Christianity—both Protestant and Catholic—and Vodou in Haiti is marked by a high degree of combativeness, hostility, and discomfort. To resolve the religious tension between Haitian Vodou and Haitian Christianity, Hurbon has suggested a frank ecumenical dialogue between Vodou, Catholicism, and Protestantism, and carefully demonstrated the legitimation of Vodou in the Haitian experience and life. In the same line of thought, Fils-Aimé has recommended an interreligious dialogue between the two religious traditions, and brilliantly argued for the inculturation of the Vodou faith in Haitian Protestantism and culture. Through their work, both thinkers continue to campaign for more religious tolerance, pluralism, and religious inclusivism in Haitian society. I am suggesting that the Catholic theologian Laënnec Hurbon in his classic work Dieu dans le vaudou haïtien (1972) has inaugurated what we phrase the Christian–Vodouist compromissory tradition. Following the footsteps of Hurbon, Fils-Aimé in his controversial and learned work Vodou, je me souviens, published in 2007, has done for Haitian Protestantism what Hurbon has achieved for Haitian Catholicism—pushing forward the idea of the inculturation of Vodou culture and practices in Protestant Christianity in Haiti—within the framework of a Protestant–Vodouist compromissory tradition.
Canadian Studies on the Effectiveness of Community Treatment Orders
Authors: Kisely Steve 
Published: August 2016

Objectives: Community treatment orders (CTOs) for people with severe mental illnesses are used across most of Canada. It is unclear if they can reduce health service use, or improve clinical and social outcomes. This review summarizes the evidence from studies conducted in Canada. Method: A systematic literature search of PubMed and MEDLINE to March 2015 was conducted. Inclusion criteria were quantitative and qualitative studies undertaken in Canada that presented data on the effect of CTOs on outcomes. Results: Nine papers from 8 studies were included in the review. Four studies compared health service use before and after compulsory treatment as well as engagement with psychosocial supports. Three were qualitative evaluations of patients, family, or staff and the last was a postal survey of psychiatrists. Hospital readmission rates and days spent in hospital were all reduced following CTO placement, while outpatient attendance and participation in psychiatric services and housing all improved. Family members and clinicians were generally positive about the effect of CTOs but patients were ambivalent. However, the strength of the evidence was limited as many of the studies were small, only one included control subjects, and there was no adjustment for potential confounders using either matching or multivariate analyses. Only 2 qualitative studies included the views of patients and their families. Conclusions: The evidence base for the use of CTOs in Canada is limited and this lack of Canadian research is in marked contrast to other countries where there have been large studies that have used randomized or matched control subjects. Their use should be kept under review.
Factors Associated with Suicidal Thought and Help-Seeking Behaviour in Transition-Aged Youth versus Adults
Authors: MacKinnon Nathalie , Colman Ian 
Published: August 2016

Objective: Suicide is a leading cause of death for transition-aged youth (TAY), and yet few studies examine correlates of suicidal ideation specifically in this age demographic (age 18-24 years). The transition to adulthood is a unique context, marked by novel stressors (e.g., joining the workforce) and increased independence, which may influence risk factors for suicidal ideation. This study examined correlates of suicidal ideation in TAY and adults and contrasted profiles across age. Methods: We used 4 biannual cycles (2005, 2007, 2009, 2011) of the Canadian Community Health Survey, a population-based cross-sectional survey on health. We used logistic regression to assess the association between suicidal ideation and depression, distress, alcohol use, smoking, exercise, sedentary behaviour, chronic illness, restrictions to daily living, perceived physical and mental health, and perceived social support independently in both TAY ( n = 4427) and adults ( n = 14,452). We subsequently assessed possible interactions with age (18-24 v. 25-44 years) and sex and differences in help-seeking behaviour in a combined model. Result: TAY exhibited higher rates of suicidal ideation than adults did ( P < 0.001). Numerous factors were associated with suicidal ideation in TAY. Notably, alcohol abstinence was associated with decreased suicidal ideation in TAY but not for adults. Moreover, when depressed, TAY were significantly less likely to have received professional mental health help than adults (odds ratio = 0.64, 95% CI, 0.43 to 0.94). Conclusions: Suicidal ideation is more prevalent in TAY than adults, and its consequences may be aggravated by poor treatment-seeking behaviour in at-risk (i.e. depressed) individuals. These different risk profiles substantiate the recent shift toward clinical interventions focusing on transition-aged youth, rather than traditional child (<18 years) and adult (>18 years) services.
Resilience in American Indian and Alaska Native Public Health: An Underexplored Framework
Authors: Teufel-Shone Nicolette I. , Tippens Julie A. , McCrary Hilary C. , Ehiri John E. , Sanderson Priscilla R. 
Published: August 2016

Objective: To conduct a systematic literature review to assess the conceptualization, application, and measurement of resilience in American Indian and Alaska Native (AIAN) health promotion. Data Sources: We searched 9 literature databases to document how resilience is discussed, fostered, and evaluated in studies of AIAN health promotion in the United States. Study Inclusion and Exclusion Criteria: The article had to (1) be in English; (2) peer reviewed, published from January 1, 1980, to July 31, 2015; (3) identify the target population as predominantly AIANs in the United States; (4) describe a nonclinical intervention or original research that identified resilience as an outcome or resource; and (5) discuss resilience as related to cultural, social, and/or collective strengths. Data Extraction: Sixty full texts were retrieved and assessed for inclusion by 3 reviewers. Data were extracted by 2 reviewers and verified for relevance to inclusion criteria by the third reviewer. Data Synthesis: Attributes of resilience that appeared repeatedly in the literature were identified. Findings were categorized across the lifespan (age group of participants), divided by attributes, and further defined by specific domains within each attribute. Results: Nine articles (8 studies) met the criteria. Currently, resilience research in AIAN populations is limited to the identification of attributes and pilot interventions focused on individual resilience. Resilience models are not used to guide health promotion programming; collective resilience is not explored. Conclusion: Attributes of AIAN resilience should be considered in the development of health interventions. Attention to collective resilience is recommended to leverage existing assets in AIAN communities.