Statistical Computing
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Statistical Computing
Computational statistics, or statistical computing, is the bond between statistics and computer science. It means statistical methods that are enabled by using computational methods. It is the area of computational science (or scientific computing) specific to the mathematical science of statistics. This area is also developing rapidly, leading to calls that a broader concept of computing should be taught as part of general statistical education. As in traditional statistics the goal is to transform raw data into knowledge, Wegman, Edward J. âComputational Statistics: A New Agenda for Statistical Theory and Practice.€ť Journal of the Washington Academy of Sciences', vol. 78, no. 4, 1988, pp. 310–322. ''JSTOR'' but the focus lies on computer intensive statistical methods, such as cases with very large sample size and non-homogeneous data sets. The terms 'computational statistics' and 'statistical computing' are often used interchangeably, although Carlo Lauro (a former preside ...
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London School Of Economics Statistics Machine Room 1964
London is the capital and largest city of England and the United Kingdom, with a population of just under 9 million. It stands on the River Thames in south-east England at the head of a estuary down to the North Sea, and has been a major settlement for two millennia. The City of London, its ancient core and financial centre, was founded by the Romans as ''Londinium'' and retains its medieval boundaries.See also: Independent city § National capitals The City of Westminster, to the west of the City of London, has for centuries hosted the national government and parliament. Since the 19th century, the name "London" has also referred to the metropolis around this core, historically split between the counties of Middlesex, Essex, Surrey, Kent, and Hertfordshire, which largely comprises Greater London, governed by the Greater London Authority.The Greater London Authority consists of the Mayor of London and the London Assembly. The London Mayor is distinguished from the Lord Mayo ...
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Monte Carlo Simulation
Monte Carlo methods, or Monte Carlo experiments, are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results. The underlying concept is to use randomness to solve problems that might be deterministic in principle. They are often used in physical and mathematical problems and are most useful when it is difficult or impossible to use other approaches. Monte Carlo methods are mainly used in three problem classes: optimization, numerical integration, and generating draws from a probability distribution. In physics-related problems, Monte Carlo methods are useful for simulating systems with many coupled degrees of freedom, such as fluids, disordered materials, strongly coupled solids, and cellular structures (see cellular Potts model, interacting particle systems, McKean–Vlasov processes, kinetic models of gases). Other examples include modeling phenomena with significant uncertainty in inputs such as the calculation of risk in b ...
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United States
The United States of America (U.S.A. or USA), commonly known as the United States (U.S. or US) or America, is a country primarily located in North America. It consists of 50 states, a federal district, five major unincorporated territories, nine Minor Outlying Islands, and 326 Indian reservations. The United States is also in free association with three Pacific Island sovereign states: the Federated States of Micronesia, the Marshall Islands, and the Republic of Palau. It is the world's third-largest country by both land and total area. It shares land borders with Canada to its north and with Mexico to its south and has maritime borders with the Bahamas, Cuba, Russia, and other nations. With a population of over 333 million, it is the most populous country in the Americas and the third most populous in the world. The national capital of the United States is Washington, D.C. and its most populous city and principal financial center is New York City. Paleo-Americ ...
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Census
A census is the procedure of systematically acquiring, recording and calculating information about the members of a given population. This term is used mostly in connection with national population and housing censuses; other common censuses include censuses of agriculture, traditional culture, business, supplies, and traffic censuses. The United Nations (UN) defines the essential features of population and housing censuses as "individual enumeration, universality within a defined territory, simultaneity and defined periodicity", and recommends that population censuses be taken at least every ten years. UN recommendations also cover census topics to be collected, official definitions, classifications and other useful information to co-ordinate international practices. The UN's Food and Agriculture Organization (FAO), in turn, defines the census of agriculture as "a statistical operation for collecting, processing and disseminating data on the structure of agriculture, covering th ...
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Punched Card
A punched card (also punch card or punched-card) is a piece of stiff paper that holds digital data represented by the presence or absence of holes in predefined positions. Punched cards were once common in data processing applications or to directly control automated machinery. Punched cards were widely used through much of the 20th century in the data processing industry, where specialized and increasingly complex unit record equipment, unit record machines, organized into semiautomatic data processing systems, used punched cards for data input, output, and storage. The IBM 12-row/80-column punched card format came to dominate the industry. Many early digital computers used punched cards as the primary medium for input of both computer programs and Data (computing), data. While punched cards are now obsolete as a storage medium, as of 2012, some voting machines still used punched cards to record votes. They also had a significant cultural impact. History The idea of contr ...
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Electromechanical
In engineering, electromechanics combines processes and procedures drawn from electrical engineering and mechanical engineering. Electromechanics focuses on the interaction of electrical and mechanical systems as a whole and how the two systems interact with each other. This process is especially prominent in systems such as those of DC or AC rotating electrical machines which can be designed and operated to generate power from a mechanical process (generator) or used to power a mechanical effect (motor). Electrical engineering in this context also encompasses electronics engineering. Electromechanical devices are ones which have both electrical and mechanical processes. Strictly speaking, a manually operated switch is an electromechanical component due to the mechanical movement causing an electrical output. Though this is true, the term is usually understood to refer to devices which involve an electrical signal to create mechanical movement, or vice versa mechanical movement ...
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Tabulating Machine
The tabulating machine was an electromechanical machine designed to assist in summarizing information stored on punched cards. Invented by Herman Hollerith, the machine was developed to help process data for the 1890 U.S. Census. Later models were widely used for business applications such as accounting and inventory control. It spawned a class of machines, known as unit record equipment, and the data processing industry. The term "Super Computing" was used by the ''New York World'' newspaper in 1931 to refer to a large custom-built tabulator that IBM made for Columbia University. 1890 census The 1880 census had taken eight years to process. Since the U.S. Constitution mandates a census every ten years to apportion both congressional representatives and direct taxes among the states, a combination of larger staff and faster-recording systems was required. In the late 1880s Herman Hollerith, inspired by conductors using holes punched in different positions on a railway ...
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Herman Hollerith
Herman Hollerith (February 29, 1860 – November 17, 1929) was a German-American statistician, inventor, and businessman who developed an electromechanical tabulating machine The tabulating machine was an electromechanical machine designed to assist in summarizing information stored on punched cards. Invented by Herman Hollerith, the machine was developed to help process data for the 1890 U.S. Census. Later models w ... for punched cards to assist in summarizing information and, later, in accounting. His invention of the punched card tabulating machine, patented in 1884, marks the beginning of the era of mechanized binary code and semiautomatic data processing systems, and his concept dominated that landscape for nearly a century. Hollerith founded a company that was amalgamated in 1911 with several other companies to form the Computing-Tabulating-Recording Company. In 1924, the company was renamed "International Business Machines" (IBM) and became one of the largest and mos ...
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Robert Percival Porter
Robert Percival Porter (June 30, 1852 – February 28, 1917) was an American journalist, diplomat, and statistician who wrote on economic subjects. He served as Superintendent of the Census (1889–1893). In the statistical field, the first use of the term "computer" comes in an article in the ''Journal of the American Statistical Association'' archives by Porter in 1891. The article discusses about the use of Hermann Hollerith's machine in the 11th Census of the United States. Early life and education Robert Percival Porter was born in Norwich, England, June 30, 1852. His father was James Winearls Porter of Marham, Norfolk. He received his education at King Edward VI School, Norwich, and privately in the U.S. Career He removed to the United States on the death of his father in 1869, and begran active life as a school teacher in Illinois. When the ''Chicago Inter Ocean'' was founded, in 1872, he joined the staff of that paper, though his first s ...
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Generalized Additive Model
In statistics, a generalized additive model (GAM) is a generalized linear model in which the linear response variable depends linearly on unknown smooth functions of some predictor variables, and interest focuses on inference about these smooth functions. GAMs were originally developed by Trevor Hastie and Robert Tibshirani to blend properties of generalized linear models with additive models. They can be interpreted as the discriminative generalization of the naive Bayes generative model. The model relates a univariate response variable, ''Y'', to some predictor variables, ''x''''i''. An exponential family distribution is specified for Y (for example normal, binomial or Poisson distributions) along with a link function ''g'' (for example the identity or log functions) relating the expected value of ''Y'' to the predictor variables via a structure such as : g(\operatorname(Y))=\beta_0 + f_1(x_1) + f_2(x_2)+ \cdots + f_m(x_m).\,\! The functions ''f''''i'' may be functions with a s ...
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Artificial Neural Networks
Artificial neural networks (ANNs), usually simply called neural networks (NNs) or neural nets, are computing systems inspired by the biological neural networks that constitute animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons. An artificial neuron receives signals then processes them and can signal neurons connected to it. The "signal" at a connection is a real number, and the output of each neuron is computed by some non-linear function of the sum of its inputs. The connections are called ''edges''. Neurons and edges typically have a ''weight'' that adjusts as learning proceeds. The weight increases or decreases the strength of the signal at a connection. Neurons may have a threshold such that a signal is sent only if the aggregate signal crosses that threshold. Typically, ...
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Kernel Density Estimation
In statistics, kernel density estimation (KDE) is the application of kernel smoothing for probability density estimation, i.e., a non-parametric method to estimate the probability density function of a random variable based on ''kernels'' as weights. KDE answers a fundamental data smoothing problem where inferences about the population are made, based on a finite data sample. In some fields such as signal processing and econometrics it is also termed the Parzen–Rosenblatt window method, after Emanuel Parzen and Murray Rosenblatt, who are usually credited with independently creating it in its current form. One of the famous applications of kernel density estimation is in estimating the class-conditional marginal densities of data when using a naive Bayes classifier, which can improve its prediction accuracy. Definition Let (''x''1, ''x''2, ..., ''xn'') be independent and identically distributed samples drawn from some univariate distribution with an unknown density ''ƒ'' ...
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