- regression models with variable structure
- Математика: регрессионные модели с переменной структурой
Универсальный англо-русский словарь. Академик.ру. 2011.
regression models with variable structure
Смотреть что такое "regression models with variable structure" в других словарях:
Regression analysis — In statistics, regression analysis is a collective name for techniques for the modeling and analysis of numerical data consisting of values of a dependent variable (response variable) and of one or more independent variables (explanatory… … Wikipedia
Regression model validation — In statistics, model validation is possibly the most important step in the model building sequence. It is also one of the most overlooked.[citation needed] Often the validation of a model seems to consist of nothing more than quoting the R2… … Wikipedia
Linear regression — Example of simple linear regression, which has one independent variable In statistics, linear regression is an approach to modeling the relationship between a scalar variable y and one or more explanatory variables denoted X. The case of one… … Wikipedia
Robust regression — In robust statistics, robust regression is a form of regression analysis designed to circumvent some limitations of traditional parametric and non parametric methods. Regression analysis seeks to find the effect of one or more independent… … Wikipedia
Nonparametric regression — is a form of regression analysis in which the predictor does not take a predetermined form but is constructed according to information derived from the data. Nonparametric regression requires larger sample sizes than regression based on… … Wikipedia
Nonlinear regression — See Michaelis Menten kinetics for details In statistics, nonlinear regression is a form of regression analysis in which observational data are modeled by a function which is a nonlinear combination of the model parameters and depends on one or… … Wikipedia
Local regression — LOESS, or locally weighted scatterplot smoothing, is one of many modern modeling methods that build on classical methods, such as linear and nonlinear least squares regression. Modern regression methods are designed to address situations in which … Wikipedia
Predictive analytics — encompasses a variety of techniques from statistics and data mining that analyze current and historical data to make predictions about future events. Such predictions rarely take the form of absolute statements, and are more likely to be… … Wikipedia
Structural equation modeling — (SEM) is a statistical technique for testing and estimating causal relations using a combination of statistical data and qualitative causal assumptions. This definition of SEM was articulated by the geneticist Sewall Wright (1921),[1] the… … Wikipedia
Linear least squares (mathematics) — This article is about the mathematics that underlie curve fitting using linear least squares. For statistical regression analysis using least squares, see linear regression. For linear regression on a single variable, see simple linear regression … Wikipedia
Analysis of variance — In statistics, analysis of variance (ANOVA) is a collection of statistical models, and their associated procedures, in which the observed variance in a particular variable is partitioned into components attributable to different sources of… … Wikipedia
