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Berndt–Hall–Hall–Hausman Algorithm
The Berndt–Hall–Hall–Hausman (BHHH) algorithm is a numerical optimization algorithm similar to the Newton–Raphson algorithm, but it replaces the observed negative Hessian matrix with the outer product of the gradient. This approximation is based on the information matrix equality and therefore only valid while maximizing a likelihood function. The BHHH algorithm is named after the four originators: Ernst R. Berndt, Bronwyn Hall, Robert Hall, and Jerry Hausman. Usage If a nonlinear model is fitted to the data one often needs to estimate coefficients through optimization. A number of optimisation algorithms have the following general structure. Suppose that the function to be optimized is ''Q''(''β''). Then the algorithms are iterative, defining a sequence of approximations, ''βk'' given by :\beta_=\beta_-\lambda_A_\frac(\beta_),, where \beta_ is the parameter estimate at step k, and \lambda_ is a parameter (called step size) which partly determines the particular algorith ...
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Numerical Optimization
Mathematical optimization (alternatively spelled ''optimisation'') or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternatives. It is generally divided into two subfields: discrete optimization and continuous optimization. Optimization problems of sorts arise in all quantitative disciplines from computer science and engineering to operations research and economics, and the development of solution methods has been of interest in mathematics for centuries. In the more general approach, an optimization problem consists of maximizing or minimizing a real function by systematically choosing input values from within an allowed set and computing the value of the function. The generalization of optimization theory and techniques to other formulations constitutes a large area of applied mathematics. More generally, optimization includes finding "best available" values of some objective function given a define ...
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Jerry Hausman
Jerry Allen Hausman (born May 5, 1946) is the John and Jennie S. MacDonald Professor of Economics at the Massachusetts Institute of Technology and a notable econometrician. He has published numerous influential papers in microeconometrics. Hausman is the recipient of several prestigious awards including the John Bates Clark Medal in 1985 and the Frisch Medal in 1980. He is perhaps most well known for his development of the Durbin-Wu-Hausman test, the first easy method allowing scientists to evaluate if their statistical models correspond to the data. He has done extensive work in the field of telecommunications, and is also recognized as an expert on antitrust and mergers, public finance and taxation, and regulation. Hausman also serves as the director of the MIT Telecommunications Economics Research Program. His recent applied papers are on topics including the effect of new goods on economic welfare and their measurement in the CPI, new telecommunications technologies incl ...
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Broyden–Fletcher–Goldfarb–Shanno Algorithm
In numerical optimization, the Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm is an iterative method for solving unconstrained nonlinear optimization problems. Like the related Davidon–Fletcher–Powell method, BFGS determines the descent direction by preconditioning the gradient with curvature information. It does so by gradually improving an approximation to the Hessian matrix of the loss function, obtained only from gradient evaluations (or approximate gradient evaluations) via a generalized secant method. Since the updates of the BFGS curvature matrix do not require matrix inversion, its computational complexity is only \mathcal(n^), compared to \mathcal(n^) in Newton's method. Also in common use is L-BFGS, which is a limited-memory version of BFGS that is particularly suited to problems with very large numbers of variables (e.g., >1000). The BFGS-B variant handles simple box constraints. The algorithm is named after Charles George Broyden, Roger Fletcher, ...
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Newton–Raphson
In numerical analysis, Newton's method, also known as the Newton–Raphson method, named after Isaac Newton and Joseph Raphson, is a root-finding algorithm which produces successively better approximations to the roots (or zeroes) of a real-valued function. The most basic version starts with a single-variable function defined for a real variable , the function's derivative , and an initial guess for a root of . If the function satisfies sufficient assumptions and the initial guess is close, then :x_ = x_0 - \frac is a better approximation of the root than . Geometrically, is the intersection of the -axis and the tangent of the graph of at : that is, the improved guess is the unique root of the linear approximation at the initial point. The process is repeated as :x_ = x_n - \frac until a sufficiently precise value is reached. This algorithm is first in the class of Householder's methods, succeeded by Halley's method. The method can also be extended to complex functions an ...
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Optimization (mathematics)
Mathematical optimization (alternatively spelled ''optimisation'') or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternatives. It is generally divided into two subfields: discrete optimization and continuous optimization. Optimization problems of sorts arise in all quantitative disciplines from computer science and engineering to operations research and economics, and the development of solution methods has been of interest in mathematics for centuries. In the more general approach, an optimization problem consists of maximizing or minimizing a real function by systematically choosing input values from within an allowed set and computing the value of the function. The generalization of optimization theory and techniques to other formulations constitutes a large area of applied mathematics. More generally, optimization includes finding "best available" values of some objective function given a define ...
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Coefficient
In mathematics, a coefficient is a multiplicative factor in some term of a polynomial, a series, or an expression; it is usually a number, but may be any expression (including variables such as , and ). When the coefficients are themselves variables, they may also be called parameters. For example, the polynomial 2x^2-x+3 has coefficients 2, −1, and 3, and the powers of the variable x in the polynomial ax^2+bx+c have coefficient parameters a, b, and c. The constant coefficient is the coefficient not attached to variables in an expression. For example, the constant coefficients of the expressions above are the number 3 and the parameter ''c'', respectively. The coefficient attached to the highest degree of the variable in a polynomial is referred to as the leading coefficient. For example, in the expressions above, the leading coefficients are 2 and ''a'', respectively. Terminology and definition In mathematics, a coefficient is a multiplicative factor in some term of a ...
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Data
In the pursuit of knowledge, data (; ) is a collection of discrete values that convey information, describing quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted. A datum is an individual value in a collection of data. Data is usually organized into structures such as tables that provide additional context and meaning, and which may themselves be used as data in larger structures. Data may be used as variables in a computational process. Data may represent abstract ideas or concrete measurements. Data is commonly used in scientific research, economics, and in virtually every other form of human organizational activity. Examples of data sets include price indices (such as consumer price index), unemployment rates, literacy rates, and census data. In this context, data represents the raw facts and figures which can be used in such a manner in order to capture the useful information out of it. ...
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Nonlinear
In mathematics and science, a nonlinear system is a system in which the change of the output is not proportional to the change of the input. Nonlinear problems are of interest to engineers, biologists, physicists, mathematicians, and many other scientists because most systems are inherently nonlinear in nature. Nonlinear dynamical systems, describing changes in variables over time, may appear chaotic, unpredictable, or counterintuitive, contrasting with much simpler linear systems. Typically, the behavior of a nonlinear system is described in mathematics by a nonlinear system of equations, which is a set of simultaneous equations in which the unknowns (or the unknown functions in the case of differential equations) appear as variables of a polynomial of degree higher than one or in the argument of a function which is not a polynomial of degree one. In other words, in a nonlinear system of equations, the equation(s) to be solved cannot be written as a linear combination of the un ...
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Robert Hall (economist)
Robert Ernest "Bob" Hall (born August 13, 1943) is an American economist and a Robert and Carole McNeil Senior Fellow at Stanford University's Hoover Institution. He is generally considered a macroeconomist, but he describes himself as an "applied economist". Hall received a BA in economics at the University of California, Berkeley, and a PhD in economics from MIT for a thesis titled ''Essays on the Theory of Wealth'' under the supervision of Robert Solow. Hall is a member of the Hoover Institution, the National Academy of Sciences, a fellow at both American Academy of Arts and Sciences and the Econometric Society, and a member of the NBER. He is the chairman of the Business Cycle Dating Committee, the body responsible for setting the start and end dates of U.S. economic recessions. Hall served as president of the American Economic Association in 2010, and is a long-time member of the Brookings Panel on Economic Activity. Ideas Hall has a broad range of interests, includi ...
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Algorithm
In mathematics and computer science, an algorithm () is a finite sequence of rigorous instructions, typically used to solve a class of specific Computational problem, problems or to perform a computation. Algorithms are used as specifications for performing calculations and data processing. More advanced algorithms can perform automated deductions (referred to as automated reasoning) and use mathematical and logical tests to divert the code execution through various routes (referred to as automated decision-making). Using human characteristics as descriptors of machines in metaphorical ways was already practiced by Alan Turing with terms such as "memory", "search" and "stimulus". In contrast, a Heuristic (computer science), heuristic is an approach to problem solving that may not be fully specified or may not guarantee correct or optimal results, especially in problem domains where there is no well-defined correct or optimal result. As an effective method, an algorithm ca ...
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Bronwyn Hall
Bronwyn Hughes Hall is the Emerita Professor of Economics at the University of California at Berkeley. Education Hall received a B.A. in Physics from Wellesley College in 1966 and a Ph.D. in economics from Stanford University in 1988. Career She was professor of economics of technology and innovation at Maastricht University between 2005 and 2015. Hall founded TSP International, an econometric software firm, from which she has severed ties. Hall is a research associate of the National Bureau of Economic Research and the Institute for Fiscal Studies. She is also a visiting fellow at the National Institute of Economic and Social Research. Bibliography * * * References External links Faculty page* on IDEAS/RePEc Profileon Academia.edu Academia.edu is a for-profit open repository of academic articles free to read by visitors. Uploading and downloading is restricted to registered users. Additional features are accessible only as a paid subscription. Since 2016 various soc ...
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