Peter Whittle (mathematician)
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Peter Whittle (mathematician)
Peter Whittle (27 February 1927 – 10 August 2021) was a mathematician and statistician from New Zealand, working in the fields of stochastic nets, optimal control, time series analysis, stochastic optimisation and stochastic dynamics. From 1967 to 1994, he was the Churchill Professor of Mathematics for Operational Research at the University of Cambridge. Career Whittle was born in Wellington. He graduated from the University of New Zealand in 1947 with a BSc in mathematics and physics and in 1948 with an MSc in mathematics. He then moved to Uppsala, Sweden in 1950 to study for his PhD with Herman Wold (at Uppsala University). His thesis, ''Hypothesis Testing in Time Series'', generalised Wold's autoregressive representation theorem for univariate stationary processes to multivariate processes. Whittle's thesis was published in 1951. A synopsis of Whittle's thesis also appeared as an appendix to the second edition of Wold's book on time-series analysis. Whittle re ...
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Wellington
Wellington ( mi, Te Whanganui-a-Tara or ) is the capital city of New Zealand. It is located at the south-western tip of the North Island, between Cook Strait and the Remutaka Range. Wellington is the second-largest city in New Zealand by metro area, and is the administrative centre of the Wellington Region. It is the world's southernmost capital of a sovereign state. Wellington features a temperate maritime climate, and is the world's windiest city by average wind speed. Legends recount that Kupe discovered and explored the region in about the 10th century, with initial settlement by Māori iwi such as Rangitāne and Muaūpoko. The disruptions of the Musket Wars led to them being overwhelmed by northern iwi such as Te Āti Awa by the early 19th century. Wellington's current form was originally designed by Captain William Mein Smith, the first Surveyor General for Edward Wakefield's New Zealand Company, in 1840. The Wellington urban area, which only includes urbanised ar ...
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Statistical Hypothesis Testing
A statistical hypothesis test is a method of statistical inference used to decide whether the data at hand sufficiently support a particular hypothesis. Hypothesis testing allows us to make probabilistic statements about population parameters. History Early use While hypothesis testing was popularized early in the 20th century, early forms were used in the 1700s. The first use is credited to John Arbuthnot (1710), followed by Pierre-Simon Laplace (1770s), in analyzing the human sex ratio at birth; see . Modern origins and early controversy Modern significance testing is largely the product of Karl Pearson ( ''p''-value, Pearson's chi-squared test), William Sealy Gosset ( Student's t-distribution), and Ronald Fisher ("null hypothesis", analysis of variance, "significance test"), while hypothesis testing was developed by Jerzy Neyman and Egon Pearson (son of Karl). Ronald Fisher began his life in statistics as a Bayesian (Zabell 1992), but Fisher soon grew disenchanted with t ...
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John Von Neumann Theory Prize
The John von Neumann Theory Prize of the Institute for Operations Research and the Management Sciences (INFORMS) is awarded annually to an individual (or sometimes a group) who has made fundamental and sustained contributions to theory in operations research and the management sciences. The Prize named after mathematician John von Neumann is awarded for a body of work, rather than a single piece. The Prize was intended to reflect contributions that have stood the test of time. The criteria include significance, innovation, depth, and scientific excellence. The award is $5,000, a medallion and a citation. The Prize has been awarded since 1975. The first recipient was George B. Dantzig for his work on linear programming. List of recipients * 2022 Vijay Vazirani * 2021 Alexander Shapiro * 2020 Adrian Lewis * 2019 Dimitris Bertsimas and Jong-Shi Pang * 2018 Dimitri Bertsekas and John Tsitsiklis ** ''for contributions to Parallel and Distributed Computation as well as Neurodynam ...
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Sylvester Medal
The Sylvester Medal is a bronze medal awarded by the Royal Society (London) for the encouragement of mathematical research, and accompanied by a £1,000 prize. It was named in honour of James Joseph Sylvester, the Savilian Professor of Geometry at the University of Oxford in the 1880s, and first awarded in 1901, having been suggested by a group of Sylvester's friends (primarily Raphael Meldola) after his death in 1897. Initially awarded every three years with a prize of around £900, the Royal Society have announced that starting in 2009 it will be awarded every two years instead, and is to be aimed at 'early to mid career stage scientist' rather than an established mathematician. The award winner is chosen by the Society's A-side awards committee, which handles physical rather than biological science awards. , 45 medals have been awarded, of which all but 10 have been awarded to citizens of the United Kingdom, two to citizens of France and United States, and one medal each has be ...
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Guy Medal
The Guy Medals are awarded by the Royal Statistical Society in three categories; Gold, Silver and Bronze. The Silver and Bronze medals are awarded annually. The Gold Medal was awarded every three years between 1987 and 2011, but is awarded biennially as of 2019. They are named after William Guy. *The Guy Medal in Gold is awarded to fellows or others who are judged to have merited a signal mark of distinction by reason of their innovative contributions to the theory or application of statistics. *The Guy Medal in Silver is awarded to any fellow or, in exceptional cases, to two or more fellows in respect of a paper/papers of special merit communicated to the Society at its ordinary meetings, or in respect of a paper/papers published in any of the journals of the Society. General contributions to statistics may also be taken into account. *The Guy Medal in Bronze is awarded to fellows, or to non-fellows who are members of a section or a local group, in respect of a paper or papers rea ...
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Royal Society Of New Zealand
Royal may refer to: People * Royal (name), a list of people with either the surname or given name * A member of a royal family Places United States * Royal, Arkansas, an unincorporated community * Royal, Illinois, a village * Royal, Iowa, a city * Royal, Missouri, an unincorporated community * Royal, Nebraska, a village * Royal, Franklin County, North Carolina, an unincorporated area * Royal, Utah, a ghost town * Royal, West Virginia, an unincorporated community * Royal Gorge, on the Arkansas River in Colorado * Royal Township (other) Elsewhere * Mount Royal, a hill in Montreal, Canada * Royal Canal, Dublin, Ireland * Royal National Park, New South Wales, Australia Arts, entertainment, and media * ''Royal'' (Jesse Royal album), a 2021 reggae album * ''The Royal'', a British medical drama television series * ''The Royal Magazine'', a monthly British literary magazine published between 1898 and 1939 * ''Royal'' (Indian magazine), a men's lifestyle bimonthly * Royal T ...
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Fellow Of The Royal Society
Fellowship of the Royal Society (FRS, ForMemRS and HonFRS) is an award granted by the judges of the Royal Society of London to individuals who have made a "substantial contribution to the improvement of natural science, natural knowledge, including mathematics, engineering science, and medical science". Fellow, Fellowship of the Society, the oldest known scientific academy in continuous existence, is a significant honour. It has been awarded to many eminent scientists throughout history, including Isaac Newton (1672), Michael Faraday (1824), Charles Darwin (1839), Ernest Rutherford (1903), Srinivasa Ramanujan (1918), Albert Einstein (1921), Paul Dirac (1930), Winston Churchill (1941), Subrahmanyan Chandrasekhar (1944), Dorothy Hodgkin (1947), Alan Turing (1951), Lise Meitner (1955) and Francis Crick (1959). More recently, fellowship has been awarded to Stephen Hawking (1974), David Attenborough (1983), Tim Hunt (1991), Elizabeth Blackburn (1992), Tim Berners-Lee (2001), Venki R ...
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Karl Gustav Jöreskog
Karl Gustav Jöreskog (born 25 April 1935) is a Sweden, Swedish statistician. Jöreskog is a Professor Emeritus at Uppsala University, and a co-author (with Dag Sörbom) of the LISREL statistical program. He is also a member of the Royal Swedish Academy of Sciences. Jöreskog received his bachelor's, master's, and doctoral degrees in Uppsala University. He is also a former student of Herman Wold. He was a statistician at Educational Testing Service, Educational Testing Service (ETS) and a visiting professor at Princeton University. Research Jöreskog proposed a reliable numerical method for computing maximum-likelihood estimates in factor analysis; similarly reliable methods were also proposed by Gerhard Derflinger, Robert Jennrich, and Stephen M. Robinson at roughly the same time. Jöreskog's Fortran codes helped to popularize factor analysis around the world. While working at the Educational Testing Service and giving lectures at Princeton University, Jöreskog proposed a linear ...
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Matérn Covariance Function
In statistics, the Matérn covariance, also called the Matérn kernel, is a covariance function used in spatial statistics, geostatistics, machine learning, image analysis, and other applications of multivariate statistical analysis on metric spaces. It is named after the Swedish forestry statistician Bertil Matérn. It specifies the covariance between two measurements as a function of the distance between the points at which they are taken. Since the covariance only depends on distances between points, it is stationary. If the distance is Euclidean distance, the Matérn covariance is also isotropic. Definition The Matérn covariance between measurements taken at two points separated by ''d'' distance units is given by Rasmussen, Carl Edward and Williams, Christopher K. I. (2006Gaussian Processes for Machine Learning/ref> : C_\nu(d) = \sigma^2\frac\Bigg(\sqrt\frac\Bigg)^\nu K_\nu\Bigg(\sqrt\frac\Bigg), where \Gamma is the gamma function, K_\nu is the modified Bessel function ...
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Maurice Bartlett
Maurice Stevenson Bartlett FRS (18 June 1910 – 8 January 2002) was an English statistician who made particular contributions to the analysis of data with spatial and temporal patterns. He is also known for his work in the theory of statistical inference and in multivariate analysis. Biography Born in London, Bartlett was raised in a poor family but won a scholarship to Latymer Upper School in Hammersmith, where he was inspired to the study of statistics by a chapter in Hall and Knight's ''Algebra''. In 1929, he won a scholarship to Queens' College, Cambridge where he read mathematics, graduating with the rank of wrangler. He attended lectures on statistics by John Wishart, on relativity by Arthur Eddington and on quantum mechanics by Paul Dirac. In one of his lectures Wishart described his geometric derivation of the Wishart distribution. Overnight Bartlett worked out a proof using characteristic functions. Bartlett was Wishart's first post-graduate student and they wro ...
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Bayesian Experimental Design
Bayesian experimental design provides a general probability-theoretical framework from which other theories on experimental design can be derived. It is based on Bayesian inference to interpret the observations/data acquired during the experiment. This allows accounting for both any prior knowledge on the parameters to be determined as well as uncertainties in observations. The theory of Bayesian experimental design is to a certain extent based on the theory for making optimal decisions under uncertainty. The aim when designing an experiment is to maximize the expected utility of the experiment outcome. The utility is most commonly defined in terms of a measure of the accuracy of the information provided by the experiment (e.g. the Shannon information or the negative of the variance), but may also involve factors such as the financial cost of performing the experiment. What will be the optimal experiment design depends on the particular utility criterion chosen. Relations to more ...
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Optimal Design
In the design of experiments, optimal designs (or optimum designs) are a class of experimental designs that are optimal with respect to some statistical criterion. The creation of this field of statistics has been credited to Danish statistician Kirstine Smith. In the design of experiments for estimating statistical models, optimal designs allow parameters to be estimated without bias and with minimum variance. A non-optimal design requires a greater number of experimental runs to estimate the parameters with the same precision as an optimal design. In practical terms, optimal experiments can reduce the costs of experimentation. The optimality of a design depends on the statistical model and is assessed with respect to a statistical criterion, which is related to the variance-matrix of the estimator. Specifying an appropriate model and specifying a suitable criterion function both require understanding of statistical theory and practical knowledge with designing exper ...
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