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Bayesian Hierarchical Modeling
Bayesian hierarchical modelling is a statistical model written in multiple levels (hierarchical form) that estimates the parametric model, parameters of the Posterior probability, posterior distribution using the Bayesian inference, Bayesian method.Allenby, Rossi, McCulloch (January 2005)"Hierarchical Bayes Model: A Practitioner’s Guide" pp. 1–4. Retrieved 26 April 2014, p. 3 The sub-models combine to form the hierarchical model, and Bayes' theorem is used to integrate them with the observed data and account for all the uncertainty that is present. The result of this integration is it allows calculation of the posterior distribution of the prior distribution, prior, providing an updated probability estimate. Frequentist statistics ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Statistical Model
A statistical model is a mathematical model that embodies a set of statistical assumptions concerning the generation of Sample (statistics), sample data (and similar data from a larger Statistical population, population). A statistical model represents, often in considerably idealized form, the Data generating process, data-generating process. When referring specifically to probability, probabilities, the corresponding term is probabilistic model. All Statistical hypothesis testing, statistical hypothesis tests and all Estimator, statistical estimators are derived via statistical models. More generally, statistical models are part of the foundation of statistical inference. A statistical model is usually specified as a mathematical relationship between one or more random variables and other non-random variables. As such, a statistical model is "a formal representation of a theory" (Herman J. Adèr, Herman Adèr quoting Kenneth A. Bollen, Kenneth Bollen). Introduction Informally, a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
George Tiao
George Ching-Hwuan Tiao (; born November 8, 1933) is an econometrician, statistician, and professor emeritus of economics and statistics at the University of Chicago Booth School of Business. He was the founding chair editor of '' Statistica Sinica''. He has contributed greatly to the field of Bayesian econometrics. Biography Tiao was born in London while both his parents were studying at the London School of Economics and raised in China. In 1950, he moved to Taiwan with his parents and studied at Nanjing Jinling High School. He earned a bachelor's degree in economics from the National Taiwan University. He moved to the United States in 1956 and earned an MBA in banking and finance from New York University in 1958. He earned his PhD in economics from the University of Wisconsin–Madison in 1962. His doctoral advisors were Roger Frederick Miller and George E. P. Box. After graduating, he worked as a faculty member for twenty years at the University of Wisconsin, serving as chai ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
George E
George may refer to: Names * George (given name) * George (surname) People * George (singer), American-Canadian singer George Nozuka, known by the mononym George * George Papagheorghe, also known as Jorge / GEØRGE * George, stage name of Giorgio Moroder * George, son of Andrew I of Hungary Places South Africa * George, South Africa, a city ** George Airport United States * George, Iowa, a city * George, Missouri, a ghost town * George, Washington, a city * George County, Mississippi * George Air Force Base, a former U.S. Air Force base located in California Computing * George (algebraic compiler) also known as 'Laning and Zierler system', an algebraic compiler by Laning and Zierler in 1952 * GEORGE (computer), early computer built by Argonne National Laboratory in 1957 * GEORGE (operating system), a range of operating systems (George 1–4) for the ICT 1900 range of computers in the 1960s * GEORGE (programming language), an autocode system invented by Charles Le ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Grade Point Average
Grading in education is the application of standardized Measurement, measurements to evaluate different levels of student achievement in a course. Grades can be expressed as letters (usually A to F), as a range (for example, 1 to 6), percentages, or as numbers out of a possible total (often out of 100). The exact system that is used varies worldwide. Significance In some countries, grades are averaged to create a grade point average (GPA). GPA is calculated by using the number of grade points a student earns in a given period of time. A GPA is often calculated for high school, undergraduate, and graduate school, graduate students. A cumulative grade point average (CGPA) is the average of all the GPAs a student has achieved during their time at the institution. Students are sometimes required to maintain a certain GPA in order to be admitted to a certain academic program or to remain in that program. Grades are also used in decisions to provide a student with financial aid or ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Normal Distribution
In probability theory and statistics, a normal distribution or Gaussian distribution is a type of continuous probability distribution for a real-valued random variable. The general form of its probability density function is f(x) = \frac e^\,. The parameter is the mean or expectation of the distribution (and also its median and mode), while the parameter \sigma^2 is the variance. The standard deviation of the distribution is (sigma). A random variable with a Gaussian distribution is said to be normally distributed, and is called a normal deviate. Normal distributions are important in statistics and are often used in the natural and social sciences to represent real-valued random variables whose distributions are not known. Their importance is partly due to the central limit theorem. It states that, under some conditions, the average of many samples (observations) of a random variable with finite mean and variance is itself a random variable—whose distribution c ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Tilde
The tilde (, also ) is a grapheme or with a number of uses. The name of the character came into English from Spanish , which in turn came from the Latin , meaning 'title' or 'superscription'. Its primary use is as a diacritic (accent) in combination with a base letter. Its freestanding form is used in modern texts mainly to indicate approximation. History Use by medieval scribes The tilde was originally one of a variety of marks written over an omitted letter or several letters as a scribal abbreviation (a "mark of contraction"). Thus, the commonly used words ''Anno Domini'' were frequently abbreviated to ''Ao Dñi'', with an elevated terminal with a contraction mark placed over the "n". Such a mark could denote the omission of one letter or several letters. This saved on the expense of the scribe's labor and the cost of vellum and ink. Medieval European charters written in Latin are largely made up of such abbreviated words with contraction marks and other abbreviations ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Variance
In probability theory and statistics, variance is the expected value of the squared deviation from the mean of a random variable. The standard deviation (SD) is obtained as the square root of the variance. Variance is a measure of dispersion, meaning it is a measure of how far a set of numbers is spread out from their average value. It is the second central moment of a distribution, and the covariance of the random variable with itself, and it is often represented by \sigma^2, s^2, \operatorname(X), V(X), or \mathbb(X). An advantage of variance as a measure of dispersion is that it is more amenable to algebraic manipulation than other measures of dispersion such as the expected absolute deviation; for example, the variance of a sum of uncorrelated random variables is equal to the sum of their variances. A disadvantage of the variance for practical applications is that, unlike the standard deviation, its units differ from the random variable, which is why the standard devi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Mean
A mean is a quantity representing the "center" of a collection of numbers and is intermediate to the extreme values of the set of numbers. There are several kinds of means (or "measures of central tendency") in mathematics, especially in statistics. Each attempts to summarize or typify a given group of data, illustrating the magnitude and sign of the data set. Which of these measures is most illuminating depends on what is being measured, and on context and purpose. The ''arithmetic mean'', also known as "arithmetic average", is the sum of the values divided by the number of values. The arithmetic mean of a set of numbers ''x''1, ''x''2, ..., x''n'' is typically denoted using an overhead bar, \bar. If the numbers are from observing a sample of a larger group, the arithmetic mean is termed the '' sample mean'' (\bar) to distinguish it from the group mean (or expected value) of the underlying distribution, denoted \mu or \mu_x. Outside probability and statistics, a wide rang ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Hyperprior
In Bayesian statistics, a hyperprior is a prior distribution on a hyperparameter, that is, on a parameter of a prior distribution. As with the term ''hyperparameter,'' the use of ''hyper'' is to distinguish it from a prior distribution of a parameter of the model for the underlying system. They arise particularly in the use of hierarchical models. For example, if one is using a beta distribution to model the distribution of the parameter ''p'' of a Bernoulli distribution, then: * The Bernoulli distribution (with parameter ''p'') is the ''model'' of the underlying system; * ''p'' is a ''parameter'' of the underlying system (Bernoulli distribution); * The beta distribution (with parameters ''α'' and ''β'') is the ''prior'' distribution of ''p''; * ''α'' and ''β'' are parameters of the prior distribution (beta distribution), hence ''hyperparameters;'' * A prior distribution of ''α'' and ''β'' is thus a ''hyperprior.'' In principle, one can iterate the above: if the hyperpri ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Hyperparameter (Bayesian Statistics)
In Bayesian statistics, a hyperparameter is a parameter of a prior distribution; the term is used to distinguish them from parameters of the model for the underlying system under analysis. For example, if one is using a beta distribution to model the distribution of the parameter ''p'' of a Bernoulli distribution, then: * ''p'' is a parameter of the underlying system (Bernoulli distribution), and * ''α'' and ''β'' are parameters of the prior distribution (beta distribution), hence ''hyper''parameters. One may take a single value for a given hyperparameter, or one can iterate and take a probability distribution on the hyperparameter itself, called a hyperprior. Purpose One often uses a prior which comes from a parametric family of probability distributions – this is done partly for explicitness (so one can write down a distribution, and choose the form by varying the hyperparameter, rather than trying to produce an arbitrary function), and partly so that one can ''vary' ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
