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Local Regression
Local regression or local polynomial regression, also known as moving regression, is a generalization of the moving average and polynomial regression. Its most common methods, initially developed for scatterplot smoothing, are LOESS (locally estimated scatterplot smoothing) and LOWESS (locally weighted scatterplot smoothing), both pronounced . They are two strongly related non-parametric regression methods that combine multiple regression models in a ''k''-nearest-neighbor-based meta-model. In some fields, LOESS is known and commonly referred to as Savitzky–Golay filter (proposed 15 years before LOESS). LOESS and LOWESS thus build on "classical" methods, such as linear and nonlinear least squares regression. They address situations in which the classical procedures do not perform well or cannot be effectively applied without undue labor. LOESS combines much of the simplicity of linear least squares regression with the flexibility of nonlinear regression. It does this b ...
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Loess Curve
Local regression or local polynomial regression, also known as moving regression, is a generalization of the moving average and polynomial regression. Its most common methods, initially developed for scatterplot smoothing, are LOESS (locally estimated scatterplot smoothing) and LOWESS (locally weighted scatterplot smoothing), both pronounced . They are two strongly related non-parametric regression methods that combine multiple regression models in a k-nearest neighbor algorithm, ''k''-nearest-neighbor-based meta-model. In some fields, LOESS is known and commonly referred to as Savitzky–Golay filter (proposed 15 years before LOESS). LOESS and LOWESS thus build on classical statistics, "classical" methods, such as linear and nonlinear least squares regression. They address situations in which the classical procedures do not perform well or cannot be effectively applied without undue labor. LOESS combines much of the simplicity of linear least squares regression with the flexibi ...
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David Bellhouse (statistician)
David Bellhouse (February 8, 1764 – 1840) was an English builder who did much to shape Victorian-era Manchester, both physically and socially. Biography Born in Leeds, Bellhouse received no formal education. An autodidact, he taught himself to read and write and the elements of arithmetic and technical drawing. In 1786, he moved to Manchester where he married Mary Wainwright and took up employment as a joiner with the building firm of Thomas Sharp. Sharp died in 1803 and his family had little appetite for the business so it was acquired by Bellhouse. During the Industrial Revolution there was a mass movement of workers towards Manchester to take up employment in the cotton spinning and textile industry. This created a demand for cheap housing and Bellhouse and his partners were among several tradesmen builders who made their fortunes in property speculation. From the early nineteenth century, Bellhouse expanded into the construction of complete factories and into work as a su ...
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Generalized Linear Model
In statistics, a generalized linear model (GLM) is a flexible generalization of ordinary linear regression. The GLM generalizes linear regression by allowing the linear model to be related to the response variable via a ''link function'' and by allowing the magnitude of the variance of each measurement to be a function of its predicted value. Generalized linear models were formulated by John Nelder and Robert Wedderburn as a way of unifying various other statistical models, including linear regression, logistic regression and Poisson regression. They proposed an iteratively reweighted least squares method for maximum likelihood estimation (MLE) of the model parameters. MLE remains popular and is the default method on many statistical computing packages. Other approaches, including Bayesian regression and least squares fitting to variance stabilized responses, have been developed. Intuition Ordinary linear regression predicts the expected value of a given unknown quanti ...
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Trevor Hastie
Trevor John Hastie (born 27 June 1953) is an American statistician and computer scientist. He is currently serving as the John A. Overdeck Professor of Mathematical Sciences and Professor of Statistics at Stanford University. Hastie is known for his contributions to applied statistics, especially in the field of machine learning, data mining, and bioinformatics. He has authored several popular books in statistical learning, including ''The Elements of Statistical Learning: Data Mining, Inference, and Prediction''. Hastie has been listed as an ISI Highly Cited Author in Mathematics by the ISI Web of Knowledge. He also contributed to the development of S. Education and career Hastie was born on 27 June 1953 in South Africa. He received his B.S. in statistics from the Rhodes University in 1976 and master's degree from University of Cape Town in 1979. Hastie joined the doctoral program at Stanford University in 1980 and received his Ph.D. in 1984 under the supervision of Werner St ...
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Robert Tibshirani
Robert Tibshirani (born July 10, 1956) is a professor in the Departments of Statistics and Biomedical Data Science at Stanford University. He was a professor at the University of Toronto from 1985 to 1998. In his work, he develops statistical tools for the analysis of complex datasets, most recently in genomics and proteomics. His most well-known contributions are the Lasso method, which proposed the use of L1 penalization in regression and related problems, and Significance Analysis of Microarrays. Education and early life Tibshirani was born on 10 July 1956 in Niagara Falls, Ontario, Canada. He received his B. Math. in statistics and computer science from the University of Waterloo in 1979 and a Master's degree in Statistics from the University of Toronto in 1980. Tibshirani joined the doctoral program at Stanford University in 1981 and received his Ph.D. in 1984 under the supervision of Bradley Efron. His dissertation was entitled "Local likelihood estimation". Honors ...
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Matthew P
Matthew may refer to: * Matthew (given name) * Matthew (surname) * ''Matthew'' (album), a 2000 album by rapper Kool Keith * Matthew (elm cultivar), a cultivar of the Chinese Elm ''Ulmus parvifolia'' Christianity * Matthew the Apostle, one of the apostles of Jesus * Gospel of Matthew, a book of the Bible Ships * ''Matthew'' (1497 ship), the ship sailed by John Cabot in 1497, with two 1990s replicas * MV ''Matthew I'', a suspected drug-runner scuttled in 2013 * Interdiction of MV ''Matthew'', a 2023 operation of the Irish military against a 2001 Panamanian cargo ship See also * Matt (given name), the diminutive form of Matthew * Mathew, alternative spelling of Matthew * Matthews (other) * Matthew effect The Matthew effect, sometimes called the Matthew principle or cumulative advantage, is the tendency of individuals to accrue social or economic success in proportion to their initial level of popularity, friends, and wealth. It is sometimes summar ... * Tropic ...
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David Ruppert
David (; , "beloved one") was a king of ancient Israel and Judah and the third king of the United Monarchy, according to the Hebrew Bible and Old Testament. The Tel Dan stele, an Aramaic-inscribed stone erected by a king of Aram-Damascus in the late 9th/early 8th centuries BCE to commemorate a victory over two enemy kings, contains the phrase (), which is translated as "House of David" by most scholars. The Mesha Stele, erected by King Mesha of Moab in the 9th century BCE, may also refer to the "House of David", although this is disputed. According to Jewish works such as the ''Seder Olam Rabbah'', ''Seder Olam Zutta'', and ''Sefer ha-Qabbalah'' (all written over a thousand years later), David ascended the throne as the king of Judah in 885 BCE. Apart from this, all that is known of David comes from biblical literature, the historicity of which has been extensively challenged,Writing and Rewriting the Story of Solomon in Ancient Israel; by Isaac Kalimi; page 32; Cambr ...
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Irène Gijbels
Irène Gijbels is a mathematical statistician at KU Leuven in Belgium, and an expert on nonparametric statistics. She has also collaborated with TopSportLab, a KU Leuven spin-off, on software for risk assessment of Sports injury, sports injuries. Education and career Gijbels earned her Ph.D. in 1990 from University of Hasselt, Limburgs Universitair Centrum. Her dissertation, supervised by Noël Veraverbeke, was ''Asymptotic Representations under Random Censoring''. She joined KU Leuven after postdoctoral research as a Fulbright scholar at the University of North Carolina at Chapel Hill and the Mathematical Sciences Research Institute. Book With Jianqing Fan, Gijbels is the author of ''Local Polynomial Modelling and Its Applications'' (CRC Press, 1996). Recognition Gijbels is an elected member of the International Statistical Institute and the Royal Flemish Academy of Belgium for Science and the Arts, and a fellow of the American Statistical Association and the Institute of Mathe ...
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Jianqing Fan
Jianqing Fan (; born 1962) is a Chinese statistician, financial econometrician, and data scientist. He is currently the Frederick L. Moore '18 Professor of Finance, Professor of Operations Research and Financial Engineering, Professor of Statistics and Machine Learning, and a former chairman of Department of Operations Research and Financial Engineering (2012–2015) and a former director of Committee of Statistical Studies (2005–2017) at Princeton University, where he directs both statistics lab and financial econometrics lab since 2008. Career Jianqing Fan is a co-editor of ''Journal of the American Statistical Association'' (2023–). He was the co-editor of '' The Annals of Statistics'' (2004–2006), a co-editor of '' Econometrics Journal'' (2007–2012), a co-editor and managing editor of ''Journal of Econometrics'' (2012–2018), co-editor of '' Journal of Business & Economic Statistics'' (2018–2021) and an editor of ''Probability Theory and Related Fields'' (2003–200 ...
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Vladimir Katkovnik
Vladimir (, , pre-1918 orthography: ) is a masculine given name of Slavic origin, widespread throughout all Slavic nations in different forms and spellings. The earliest record of a person with the name is Vladimir of Bulgaria (). Etymology The Old East Slavic form of the name is Володимѣръ ''Volodiměr'', while the Old Church Slavonic form is ''Vladiměr''. According to Max Vasmer, the name is composed of Slavic владь ''vladĭ'' "to rule" and ''*mēri'' "great", "famous" (related to Gothic element ''mērs'', ''-mir'', cf. Theode''mir'', Vala''mir''). The modern ( pre-1918) Russian forms Владимиръ and Владиміръ are based on the Church Slavonic one, with the replacement of мѣръ by миръ or міръ resulting from a folk etymological association with миръ "peace" or міръ "world". Max Vasmer, ''Etymological Dictionary of Russian Language'' s.v. "Владимир"starling.rinet.ru
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Charles Joel Stone
Charles "Chuck" Joel Stone (July 13, 1936 – April 16, 2019) was an American statistician and mathematician. Early life Charles Joel Stone was born and raised in Los Angeles. After secondary school at North Hollywood High School, Stone graduated with a Bachelor of Science in science from the California Institute of Technology in 1958. He then matriculated at Stanford University, where in 1961 he received his PhD in statistics. His PhD thesis ''Limit Theorems for Birth and Death Processes and Diffusion Processes'' was supervised by Samuel Karlin. Career From 1962 to 1964 Stone was an assistant professor in the mathematics department of Cornell University. From 1964 1981 to he was a faculty member of the mathematics department of UCLA (University of California, Los Angeles), where he worked extensively with Leo Breiman (who moved to Berkeley in 1980) and Sidney Charles Port (born 1935). In the statistics department of the University of California, Berkeley, Stone was from 1981 a ...
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Convolution
In mathematics (in particular, functional analysis), convolution is a operation (mathematics), mathematical operation on two function (mathematics), functions f and g that produces a third function f*g, as the integral of the product of the two functions after one is reflected about the y-axis and shifted. The term ''convolution'' refers to both the resulting function and to the process of computing it. The integral is evaluated for all values of shift, producing the convolution function. The choice of which function is reflected and shifted before the integral does not change the integral result (see #Properties, commutativity). Graphically, it expresses how the 'shape' of one function is modified by the other. Some features of convolution are similar to cross-correlation: for real-valued functions, of a continuous or discrete variable, convolution f*g differs from cross-correlation f \star g only in that either f(x) or g(x) is reflected about the y-axis in convolution; thus i ...
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