Regression Analysis Of Time Series
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Regression Analysis Of Time Series
RATS, an abbreviation of Regression Analysis of Time Series, is a statistical package for time series analysis and econometrics. RATS is developed and sold by Estima, Inc., located in Evanston, IL. History The forerunner of RATS was a FORTRAN program called SPECTRE, written by economist Christopher A. Sims. SPECTRE was designed to overcome some limitations of existing software that affected Sims' research in the 1970s, by providing spectral analysis and also the ability to run long unrestricted distributed lags. The program was then expanded by Tom Doan, then of the Federal Reserve Bank of Minneapolis, who added ARIMA and VAR capabilities and went on to found the consulting firm that owns and distributes RATS software. In its early incarnations, RATS was designed primarily for time series analysis, but as it evolved, it acquired other capabilities. With the advent of personal computers in 1984, RATS went from being a specialty mainframe program to an econometrics package sol ...
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Cross-platform
In computing, cross-platform software (also called multi-platform software, platform-agnostic software, or platform-independent software) is computer software that is designed to work in several computing platforms. Some cross-platform software requires a separate build for each platform, but some can be directly run on any platform without special preparation, being written in an interpreted language or compiled to portable bytecode for which the interpreters or run-time packages are common or standard components of all supported platforms. For example, a cross-platform application may run on Microsoft Windows, Linux, and macOS. Cross-platform software may run on many platforms, or as few as two. Some frameworks for cross-platform development are Codename One, Kivy, Qt, Flutter, NativeScript, Xamarin, Phonegap, Ionic, and React Native. Platforms ''Platform'' can refer to the type of processor (CPU) or other hardware on which an operating system (OS) or application runs, t ...
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Mainframe Computer
A mainframe computer, informally called a mainframe or big iron, is a computer used primarily by large organizations for critical applications like bulk data processing for tasks such as censuses, industry and consumer statistics, enterprise resource planning, and large-scale transaction processing. A mainframe computer is large but not as large as a supercomputer and has more processing power than some other classes of computers, such as minicomputers, servers, workstations, and personal computers. Most large-scale computer-system architectures were established in the 1960s, but they continue to evolve. Mainframe computers are often used as servers. The term ''mainframe'' was derived from the large cabinet, called a ''main frame'', that housed the central processing unit and main memory of early computers. Later, the term ''mainframe'' was used to distinguish high-end commercial computers from less powerful machines. Design Modern mainframe design is characterized less b ...
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Regression And Curve Fitting Software
Regression or regressions may refer to: Science * Marine regression, coastal advance due to falling sea level, the opposite of marine transgression * Regression (medicine), a characteristic of diseases to express lighter symptoms or less extent (mainly for tumors), without disappearing totally * Regression (psychology), a defensive reaction to some unaccepted impulses * Nodal regression, the movement of the nodes of an object in orbit, in the opposite direction to the motion of the object Statistics * Regression analysis, a statistical technique for estimating the relationships among variables. There are several types of regression: ** Linear regression ** Simple linear regression ** Logistic regression ** Nonlinear regression ** Nonparametric regression ** Robust regression ** Stepwise regression * Regression toward the mean, a common statistical phenomenon Computing * Software regression, the appearance of a bug which was absent in a previous revision ** Regression testing, a s ...
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Journal Of Economic Perspectives
The ''Journal of Economic Perspectives'' (JEP) is an economic journal published by the American Economic Association. The journal was established in 1987. It is very broad in its scope. According to its editors its purpose is: #to synthesize and integrate lessons learned from active lines of economic research; #to provide economic analysis of public policy issues; to encourage cross-fertilization of ideas among the fields of thinking; #to offer readers an accessible source for state-of-the-art economic thinking; #to suggest directions for future research; #to provide insights and readings for classroom use; #and to address issues relating to the economics profession.'' Its current editor is Heidi Williams, and its managing editor A managing editor (ME) is a senior member of a publication's management team. Typically, the managing editor reports directly to the editor-in-chief and oversees all aspects of the publication. United States In the United States, a managing edit ...
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Comparison Of Statistical Packages
The following tables compare general and technical information for a number of statistical analysis packages. General information Operating system support ANOVA Support for various ANOVA methods Regression Support for various Regression analysis, regression methods. Time series analysis Support for various time series analysis methods. Charts and diagrams Support for various statistical charts and diagrams. Other abilities See also * Comparison of computer algebra systems * Comparison of deep learning software * Comparison of numerical-analysis software * Comparison of survey software * Comparison of Gaussian process software * List of scientific journals in statistics * List of statistical packages Footnotes References Further reading

* * * * * {{Statistical software Comparisons of mathematical software, Statistical packages Statistical software, Statistics-related lists Mathematical and quantitative methods (economics) ...
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GARCH
In econometrics, the autoregressive conditional heteroskedasticity (ARCH) model is a statistical model for time series data that describes the variance of the current error term or innovation as a function of the actual sizes of the previous time periods' error terms; often the variance is related to the squares of the previous innovations. The ARCH model is appropriate when the error variance in a time series follows an autoregressive (AR) model; if an autoregressive moving average (ARMA) model is assumed for the error variance, the model is a generalized autoregressive conditional heteroskedasticity (GARCH) model. ARCH models are commonly employed in modeling financial time series that exhibit time-varying volatility and volatility clustering, i.e. periods of swings interspersed with periods of relative calm. ARCH-type models are sometimes considered to be in the family of stochastic volatility models, although this is strictly incorrect since at time ''t'' the volatility is co ...
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ARCH
An arch is a vertical curved structure that spans an elevated space and may or may not support the weight above it, or in case of a horizontal arch like an arch dam, the hydrostatic pressure against it. Arches may be synonymous with vaults, but a vault may be distinguished as a continuous arch forming a roof. Arches appeared as early as the 2nd millennium BC in Mesopotamian brick architecture, and their systematic use started with the ancient Romans, who were the first to apply the technique to a wide range of structures. Basic concepts An arch is a pure compression form. It can span a large area by resolving forces into compressive stresses, and thereby eliminating tensile stresses. This is sometimes denominated "arch action". As the forces in the arch are transferred to its base, the arch pushes outward at its base, denominated "thrust". As the rise, i. e. height, of the arch decreases the outward thrust increases. In order to preserve arch action and prevent collapse ...
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Neural Network
A neural network is a network or circuit of biological neurons, or, in a modern sense, an artificial neural network, composed of artificial neurons or nodes. Thus, a neural network is either a biological neural network, made up of biological neurons, or an artificial neural network, used for solving artificial intelligence (AI) problems. The connections of the biological neuron are modeled in artificial neural networks as weights between nodes. A positive weight reflects an excitatory connection, while negative values mean inhibitory connections. All inputs are modified by a weight and summed. This activity is referred to as a linear combination. Finally, an activation function controls the amplitude of the output. For example, an acceptable range of output is usually between 0 and 1, or it could be −1 and 1. These artificial networks may be used for predictive modeling, adaptive control and applications where they can be trained via a dataset. Self-learning resulting from e ...
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Kalman Filter
For statistics and control theory, Kalman filtering, also known as linear quadratic estimation (LQE), is an algorithm that uses a series of measurements observed over time, including statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more accurate than those based on a single measurement alone, by estimating a joint probability distribution over the variables for each timeframe. The filter is named after Rudolf E. Kálmán, who was one of the primary developers of its theory. This digital filter is sometimes termed the ''Stratonovich–Kalman–Bucy filter'' because it is a special case of a more general, nonlinear filter developed somewhat earlier by the Soviet mathematician Ruslan Stratonovich. In fact, some of the special case linear filter's equations appeared in papers by Stratonovich that were published before summer 1960, when Kalman met with Stratonovich during a conference in Moscow. Kalman filtering has numerous tech ...
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ARIMA
Arima, officially The Royal Chartered Borough of Arima is the easternmost and second largest in area of the three boroughs of Trinidad and Tobago. It is geographically adjacent to Sangre Grande and Arouca at the south central foothills of the Northern Range. To the south is the Caroni–Arena Dam. Coterminous with Town of Arima since 1888, the borough of Arima is the fourth-largest municipality in population in the country (after Port of Spain, Chaguanas and San Fernando). The census estimated it had 33,606 residents in 2011. In 1887, the town petitioned Queen Victoria for municipal status as part of her Golden Jubilee celebration. This was granted in the following year, and Arima became a Royal Borough on 1 August 1888. Historically the third-largest town of Trinidad and Tobago, Arima is fourth since Chaguanas became the largest town in the country. Geography Climate The borough has a tropical rainforest climate (Köppen ''Af''), bordering on a tropical monsoon climate, ...
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Maximum Likelihood Estimation
In statistics, maximum likelihood estimation (MLE) is a method of estimating the parameters of an assumed probability distribution, given some observed data. This is achieved by maximizing a likelihood function so that, under the assumed statistical model, the observed data is most probable. The point in the parameter space that maximizes the likelihood function is called the maximum likelihood estimate. The logic of maximum likelihood is both intuitive and flexible, and as such the method has become a dominant means of statistical inference. If the likelihood function is differentiable, the derivative test for finding maxima can be applied. In some cases, the first-order conditions of the likelihood function can be solved analytically; for instance, the ordinary least squares estimator for a linear regression model maximizes the likelihood when all observed outcomes are assumed to have Normal distributions with the same variance. From the perspective of Bayesian inference, M ...
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Non-linear Least Squares
Non-linear least squares is the form of least squares analysis used to fit a set of ''m'' observations with a model that is non-linear in ''n'' unknown parameters (''m'' ≥ ''n''). It is used in some forms of nonlinear regression. The basis of the method is to approximate the model by a linear one and to refine the parameters by successive iterations. There are many similarities to linear least squares, but also some significant differences. In economic theory, the non-linear least squares method is applied in (i) the probit regression, (ii) threshold regression, (iii) smooth regression, (iv) logistic link regression, (v) Box-Cox transformed regressors (m(x,\theta_i) = \theta_1 + \theta_2 x^). Theory Consider a set of m data points, (x_1, y_1), (x_2, y_2), \dots, (x_m, y_m), and a curve (model function) \hat = f(x, \boldsymbol \beta), that in addition to the variable x also depends on n parameters, \boldsymbol \beta = (\beta_1, \beta_2, \dots, \beta_n), with m\ge n. ...
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