J. K. Ghosh
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J. K. Ghosh
Jayanta Kumar Ghosh (Bengali: জয়ন্ত কুমার ঘোষ, 23 May 1937 – 30 September 2017) was an Indian statistician, an emeritus professor at Indian Statistical Institute and a professor of statistics at Purdue University. Education He obtained a B.S. from Presidency College, then affiliated with the University of Calcutta, and subsequently a M.A. and a Ph.D. from the University of Calcutta under the supervision of H. K. Nandi. He started his research career in the early 1960s, studying sequential analysis as a graduate student in the department of statistics at the University of Calcutta. Research Among his best-known discoveries are the Bahadur–Ghosh–Kiefer representation (with R. R. Bahadur and Jack Kiefer) and the Ghosh–Pratt identity along with John W. Pratt. His research contributions fall within the fields of: * Bayesian inference * Asymptotics * Modeling and model selection * High dimensional data analysis * Nonparametric r ...
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Calcutta
Kolkata (, or , ; also known as Calcutta , List of renamed places in India#West Bengal, the official name until 2001) is the Capital city, capital of the Indian States and union territories of India, state of West Bengal, on the eastern bank of the Hooghly River west of the border with Bangladesh. It is the primary business, commercial, and financial hub of East India, Eastern India and the main port of communication for North-East India. According to the 2011 Indian census, Kolkata is the List of cities in India by population, seventh-most populous city in India, with a population of 45 lakh (4.5 million) residents within the city limits, and a population of over 1.41 crore (14.1 million) residents in the Kolkata metropolitan area, Kolkata Metropolitan Area. It is the List of metropolitan areas in India, third-most populous metropolitan area in India. In 2021, the Kolkata metropolitan area crossed 1.5 crore (15 million) registered voters. The ...
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John W
John is a common English name and surname: * John (given name) * John (surname) John may also refer to: New Testament Works * Gospel of John, a title often shortened to John * First Epistle of John, often shortened to 1 John * Second Epistle of John, often shortened to 2 John * Third Epistle of John, often shortened to 3 John People * John the Baptist (died c. AD 30), regarded as a prophet and the forerunner of Jesus Christ * John the Apostle (lived c. AD 30), one of the twelve apostles of Jesus * John the Evangelist, assigned author of the Fourth Gospel, once identified with the Apostle * John of Patmos, also known as John the Divine or John the Revelator, the author of the Book of Revelation, once identified with the Apostle * John the Presbyter, a figure either identified with or distinguished from the Apostle, the Evangelist and John of Patmos Other people with the given name Religious figures * John, father of Andrew the Apostle and Saint Peter * Pope Jo ...
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Shanti Swarup Bhatnagar Prize For Science And Technology
The Shanti Swarup Bhatnagar Prize for Science and Technology (SSB) is a science award in India given annually by the Council of Scientific and Industrial Research (CSIR) for notable and outstanding research, Applied science, applied or Fundamental science, fundamental, in biology, chemistry, environmental science, engineering, mathematics, medicine, and physics. The prize recognizes outstanding Indian work (according to the view of Council of Scientific and Industrial Research, CSIR awarding committee) in science and technology. It is the most coveted award in Interdisciplinarity, multidisciplinary science in India. The award is named after the founder Director of the Council of Scientific & Industrial Research, Shanti Swaroop Bhatnagar, Shanti Swarup Bhatnagar. It was first awarded in 1958. Any citizen of India engaged in research in any field of science and technology up to the age of 45 years is eligible for the prize. The prize is awarded on the basis of contributions made thr ...
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Indian Academy Of Sciences
The Indian Academy of Sciences, Bangalore was founded by Indian Physicist and Nobel Laureate C. V. Raman, and was registered as a society on 24 April 1934. Inaugurated on 31 July 1934, it began with 65 founding fellows. The first general meeting of Fellows, held on the same day, elected Raman as president, and adopted the constitution of the Academy. Objectives The aims of the Academy are to: * Promote progress in pure and applied branches of science. * Encourage important research in various branches of science. * Represent the scientific work of India internationally. * Publish work relating to scientific research initiated by the Academy, Provincial Academies, Universities and Government Scientific Institutions. * Organise meetings of Committees and Conferences to discuss papers submitted to the Academy. * Advise Government and other bodies on scientific and other matters referred to the Academy. Publications The first issue of the Academy Proceedings appeared in two ...
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Indian National Science Academy
The Indian National Science Academy (INSA) is a national academy in New Delhi for Indian scientists in all branches of science and technology. In August 2019, Dr. Chandrima Shaha was appointed as the president of Indian National Science Academy, becoming the first woman to head the INSA (for 2020–22). In 2015 INSA has constituted a junior wing for young scientists in the country named Indian National Young Academy of Sciences (INYAS) in line with other national young academies. INYAS is the academy for young scientists in India as a national young academy and is affiliated with Global Young Academy. INYAS is also a signatory of the declaration on the Core Values of Young Academies, adopted at World Science Forum, Budapest on 20 November 2019 History The Genesis: Indian National Science Academy (INSA), New Delhi is an autonomous institution of Dept. Science & Technology, Govt. of India. However, the origins of INSA can be traced back to the founding of National Institute ...
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Institute Of Mathematical Statistics
The Institute of Mathematical Statistics is an international professional and scholarly society devoted to the development, dissemination, and application of statistics and probability. The Institute currently has about 4,000 members in all parts of the world. Beginning in 2005, the institute started offering joint membership with the Bernoulli Society for Mathematical Statistics and Probability as well as with the International Statistical Institute. The Institute was founded in 1935 with Harry C. Carver and Henry L. Rietz as its two most important supporters. The institute publishes a variety of journals, and holds several international conference every year. Publications The Institute publishes five journals: *''Annals of Statistics'' *'' Annals of Applied Statistics'' *''Annals of Probability'' *''Annals of Applied Probability'' *'' Statistical Science'' In addition, it co-sponsors: * The ''Current Index to Statistics'' * ''Electronic Communications in Probability'' * ''Ele ...
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Statistical Genetics
Statistical genetics is a scientific field concerned with the development and application of statistical methods for drawing inferences from genetic data. The term is most commonly used in the context of human genetics. Research in statistical genetics generally involves developing theory or methodology to support research in one of three related areas: *population genetics - Study of evolutionary processes affecting genetic variation between organisms *genetic epidemiology - Studying effects of genes on diseases *quantitative genetics - Studying the effects of genes on 'normal' phenotypes Statistical geneticists tend to collaborate closely with geneticists, molecular biologists, clinicians and bioinformaticians. Statistical genetics is a type of computational biology Computational biology refers to the use of data analysis, mathematical modeling and computational simulations to understand biological systems and relationships. An intersection of computer science, biology, ...
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Survival Analysis
Survival analysis is a branch of statistics for analyzing the expected duration of time until one event occurs, such as death in biological organisms and failure in mechanical systems. This topic is called reliability theory or reliability analysis in engineering, duration analysis or duration modelling in economics, and event history analysis in sociology. Survival analysis attempts to answer certain questions, such as what is the proportion of a population which will survive past a certain time? Of those that survive, at what rate will they die or fail? Can multiple causes of death or failure be taken into account? How do particular circumstances or characteristics increase or decrease the probability of survival? To answer such questions, it is necessary to define "lifetime". In the case of biological survival, death is unambiguous, but for mechanical reliability, failure may not be well-defined, for there may well be mechanical systems in which failure is partial, a matter of ...
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Density Estimation
In statistics, probability density estimation or simply density estimation is the construction of an estimate, based on observed data, of an unobservable underlying probability density function. The unobservable density function is thought of as the density according to which a large population is distributed; the data are usually thought of as a random sample from that population. A variety of approaches to density estimation are used, including Parzen windows and a range of data clustering techniques, including vector quantization. The most basic form of density estimation is a rescaled histogram. Example We will consider records of the incidence of diabetes. The following is quoted verbatim from the data set description: :''A population of women who were at least 21 years old, of Pima Indian heritage and living near Phoenix, Arizona, was tested for diabetes mellitus according to World Health Organization criteria. The data were collected by the US National Inst ...
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Nonparametric Regression
Nonparametric regression is a category of regression analysis in which the predictor does not take a predetermined form but is constructed according to information derived from the data. That is, no parametric form is assumed for the relationship between predictors and dependent variable. Nonparametric regression requires larger sample sizes than regression based on parametric models because the data must supply the model structure as well as the model estimates. Definition In nonparametric regression, we have random variables X and Y and assume the following relationship: : \mathbb \mid X=x= m(x), where m(x) is some deterministic function. Linear regression is a restricted case of nonparametric regression where m(x) is assumed to be affine. Some authors use a slightly stronger assumption of additive noise: : Y = m(X) + U, where the random variable U is the `noise term', with mean 0. Without the assumption that m belongs to a specific parametric family of functions it is impo ...
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Clustering High-dimensional Data
Clustering high-dimensional data is the cluster analysis of data with anywhere from a few dozen to many thousands of dimensions. Such high-dimensional spaces of data are often encountered in areas such as medicine, where DNA microarray technology can produce many measurements at once, and the clustering of text documents, where, if a word-frequency vector is used, the number of dimensions equals the size of the vocabulary. Problems Four problems need to be overcome for clustering in high-dimensional data: * Multiple dimensions are hard to think in, impossible to visualize, and, due to the exponential growth of the number of possible values with each dimension, complete enumeration of all subspaces becomes intractable with increasing dimensionality. This problem is known as the curse of dimensionality. * The concept of distance becomes less precise as the number of dimensions grows, since the distance between any two points in a given dataset converges. The discrimination of the near ...
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Model Selection
Model selection is the task of selecting a statistical model from a set of candidate models, given data. In the simplest cases, a pre-existing set of data is considered. However, the task can also involve the design of experiments such that the data collected is well-suited to the problem of model selection. Given candidate models of similar predictive or explanatory power, the simplest model is most likely to be the best choice (Occam's razor). state, "The majority of the problems in statistical inference can be considered to be problems related to statistical modeling". Relatedly, has said, "How hetranslation from subject-matter problem to statistical model is done is often the most critical part of an analysis". Model selection may also refer to the problem of selecting a few representative models from a large set of computational models for the purpose of decision making or optimization under uncertainty. Introduction In its most basic forms, model selection is one ...
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