Statistics

University of Calcutta (informally known as Calcutta University or CU) is a collegiate public state university located in Kolkata, West Bengal, India.&nbsp;Within India it is recognized as a &quot;Five-Star University&quot; and accredited &quot;A&quot; Grade by National Assessment and Accreditation Council.

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The University of Calcutta has secured the Fifth position among the Universities of India in the prestigious &quot;Indian University Ranking 2019&quot; list, released by the NIRF of the Ministry of Human Resource Development, Government of India.

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It was established on 24 January 1857, and was one of the first institutions in Asia to be established as a multidisciplinary and Western-style university. Its alumni and faculty include several heads of state, heads of government, social reformers, prominent artists, only academy award winner and Dirac medal winner in India, many Fellows of the Royal Society and five Nobel laureates as of 2019 which is highest in South Asia.

University Of Calcutta

We consider the problem related to clustering of gamma-ray bursts (from “BATSE” catalogue) through kernel principal component analysis in which our proposed kernel outperforms results of other competent kernels in terms of clustering accuracy and we obtain three physically interpretable groups of gamma-ray bursts. The effectivity of the suggested kernel in combination with kernel principal component analysis in revealing natural clusters in noisy and nonlinear data while reducing the dimension of the data is also explored in two simulated data sets. © 2018, © 2018 Taylor &amp; Francis Group, LLC.

GENERAL

Applied Mathematics

Fulltext

Communications in Statistics: Simulation and Computation

Clustering of gamma-ray bursts through kernel principal component analysis

An adaptive two-stage allocation design is developed for survival responses subject to independent informative censoring. The asymptotic p value of a score test related to a hypothesis of treatment effectiveness is used to set the assignment probability of the second stage. Several characteristics of the design and the follow-up inference are studied, both numerically and theoretically, and are compared with those of an existing competitor. Applicability of the proposed design is also illustrated through a real data. © 2018, © 2018 Grace Scientific Publishing, LLC.

World University root node

Journal of Statistical Theory and Practice

A two-stage adaptive allocation design for survival outcome with informative censoring

Area of study is the formation mechanism of the present-day population of elliptical galaxies, in the context of hierarchical cosmological models accompanied by ac- cretion and minor mergers. The present work investigates the formation and evolution of several components of the nearby massive early-type galaxies (ETGs) through cross- correlation function (CCF), using the spatial parameters right ascension (RA) and declination (DEC), and the intrin- sic parameters mass (M&lowast;) and size. According to the as- trophysical terminology, here these variables, namely mass, size, RA and DEC are termed as parameters, whereas the un- known constants involved in the kernel function are called hyperparameters. Throughout this paper, the parameter size is used to represent the effective radius (Re). Following Huang et al. (2013a), each nearby ETG is divided into three parts on the basis of its Re value. We study the CCF between each of these three components of nearby massive ETGs and the ETGs in the high redshift range, 0.5 &lt; z &le; 2.7. It is found that the innermost components of nearby ETGs are highly correlated with ETGs in the redshift range, 2 &lt; z &le; 2.7, known as &lsquo;red nuggets&rsquo;. The intermedi- ate and the outermost parts have moderate correlations with ETGs in the redshift range, 0.5 &lt; z &le; 0.75. The quantitative measures are highly consistent with the two phase formation scenario of nearby massive ETGs, as suggested by various authors, and resolve the conflict raised in a previous work (De et al. 2014) suggesting other possibilities for the forma- tion of the outermost part. A probable cause of this improvement is the inclusion of the spatial effects in addition to the other parameters in the study.

Astrophysics and Space Science

Two phase formation of massive elliptical galaxies: study through cross-correlation including spatial effect

During the past two decades, the interdisciplinary field of astrostatistics has newly emerged in order to study important astrophysical issues through appropriate sta- tistical analysis. Statistical analysis with missing data is an important problem as the prob- lem of incomplete information is very common in many situations. Missing values occur for a variety of reasons, from recording problems to instrument limitations. In particular, when data are combined from multiple archives or instruments, it is virtually certain that some objects will not be present in all of the contributing sources. Standard techniques of missing data analysis may not be equally applicable for astronomical data analysis as the concept of &ldquo;missing at random&rdquo; is not likely to be true for such type of data. In the present study, a review of the papers related to missing information in astronomical data and tech- niques for analysis of missing data have been considered. A new method developed by De et al. (2016) has also been discussed.

Wiley StatsRef: Statistics Reference Online

Incomplete Data in Astrostatistics

A number of allocation designs are developed for continuous and binary treatment outcomes to assign a higher number of subjects to the treatment doing better in course of the trial. However, if the response is circular in nature, the definition of a better treatment differs from that under the linear response and hence the already developed designs lack appropriateness. In the current work, redefining the notions of superiority, we develop an allocation function in the context of circular treatment outcomes. Using a response-adaptive route for practical implementation, we study the resulting design both theoretically and numerically and finally illustrate the performance for a real-life example on cataract surgery. © 2017 Grace Scientific Publishing, LLC.

An adaptive allocation design for circular treatment outcome

The association of long non-coding RNAs (lncRNAs) with dengue disease progression is currently unknown. Therefore, the present study aimed to identify lncRNAs in different categories of dengue patients and evaluate their association with dengue disease progression. Herein, we examined the expression profiles of lncRNAs and protein-coding genes between other febrile illness (OFI) and different grade of dengue patients through high-throughput RNA sequencing. We identified Nuclear Enriched Abundant Transcript 1 (NEAT1) as one of the differentially expressed lncRNAs (adjusted P ≤ 0.05 and log-fold change ≥ 2) and subsequently validated the expression by qRT-PCR. The co-expression analysis further revealed that NEAT1 and the coding gene IFI27 were highly co-expressed and negatively correlated with dengue severity. Using regression analysis, we observed that NEAT1 expression was significantly dependent on disease progression (Coefficient = −0.27750, SE Coefficient = 0.07145, and t = −3.88).Further, receiver operating characteristic (ROC) curve revealed that NEAT1 expression could discriminate DI from DS (sensitivity and specificity of 100% (95%CI: 85.69 – 97.22) and area under the curve (AUC) = 0.97). Overall, the results of this study offer the first experimental evidence demonstrating the correlation between lncRNAs and severe dengue phenotype. Monitoring NEAT1and IFI27 expression in PBMC may be useful in understanding dengue virus-induced disease progression. © 2017 The British Infection Association

Journal of Infection

Correlation of altered expression of a long non-coding RNA, NEAT1, in peripheral blood mononuclear cells with dengue disease progression

The paper investigates a M/M(b,b)/1 queuing model with bulk service. The server serves the customers in batches of fixed size b, and the service time is assumed to be exponentially distribution. Customers arrive to the system as a Poisson process and may renege after waiting in the queue for an exponentially distributed time. The reneging of a customer depends on the state of the system. The model is analyzed to find the different measures of effectiveness of the model. The approach adopted is based on embedded Markov chains. © 2017, Thai Statistical Association. All rights reserved.

Thailand Statistician

Bulk service queuing system with impatient customers: A computational approach

The problem of testing equality of means of a bivariate normal distribution on the basis of a sample of size n has been considered when the labels of the observations are either missing or not known. The problem may arise in many applied settings, especially in genetics. Classical likelihood ratio test fails here because of identifiability problems. We propose a two-stage testing procedure using a recently developed test in the context of penalized splines. The proposed testing procedure is found to outperform the tests proposed in the literature. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Statistics in Medicine

Two-stage test of means of unordered pairs

In a mixture experiment, the response depends on the mixing proportions of the components present in the mixture. Optimum designs are available for the estimation of parameters of the models proposed in such situations. However, these designs are found to include the vertex points of the simplex Ξ defining the experimental region, which are not mixtures in the true sense. Recently, Mandal et al. (2015) derived optimum designs when the experiment is confined to an ellipsoidal region within Ξ, which does not include the vertices of Ξ. In this paper, an attempt has been made to find optimum designs when the experimental region is a simplex or is cuboidal inside Ξ and does not contain the extreme points. © 2017 Taylor & Francis Group, LLC.

Communications in Statistics - Theory and Methods

Optimum mixture designs in some constrained experimental regions

In the analysis of experiments with mixtures, quadratic models have been widely used. The optimum designs for the estimation of optimum mixing proportions in a quadratic mixture model have been studied by Pal and Mandal [Optimum designs for optimum mixtures. Statist Probab Lett. 2006;76:1369–1379] and Mandal et al. [Optimum mixture designs: a pseudo-Bayesian approach. J Ind Soc Agric Stat. 2008;62(2):174–182; Optimum mixture designs under constraints on mixing components. Statist Appl. 2008;6(1&2) (New Series): 189–205], using a pseudo-Bayesian approach. In this paper, a similar approach has been employed to obtain the A-optimal designs for the estimation of optimum proportions in an additive quadratic mixture model, proposed by Darroch and Waller [Additivity and interaction in three-component experiments with mixture. Biometrika. 1985;72:153–163], when the number of components is 3, 4 and 5. It has been shown that the vertices of the simplex are necessarily the support points of the optimum design, and the other support points include barycentres of depth at most 2. © 2016 Informa UK Limited, trading as Taylor & Francis Group.