Linear predictive analysis is a simple form of first-order extrapolation: if it has been changing at this rate then it will probably continue to change...

information of a linear predictive model. LPC is the most widely used method in speech coding and speech synthesis. It is a powerful speech analysis technique...

component analysis and factor analysis. In many of these models, the coefficients are referred to as "weights". The basic form of a linear predictor function...

models and in power electronics. Model predictive controllers rely on dynamic models of the process, most often linear empirical models obtained by system...

regression analysis, linear regression focuses on the conditional probability distribution of the response given the values of the predictors, rather than...

processing, linear prediction is often called linear predictive coding (LPC) and can thus be viewed as a subset of filter theory. In system analysis, a subfield...

Linear discriminant analysis (LDA), normal discriminant analysis (NDA), canonical variates analysis (CVA), or discriminant function analysis is a generalization...

Predictive analytics encompasses a variety of statistical techniques from data mining, predictive modeling, and machine learning that analyze current...

also a method for predicting the conditional geometric mean of the response variable, .] Quantile regression is an extension of linear regression used when...

generalized linear model (GLM) is a flexible generalization of ordinary linear regression. The GLM generalizes linear regression by allowing the linear model...

statistics, a generalized linear mixed model (GLMM) is an extension to the generalized linear model (GLM) in which the linear predictor contains random effects...

models the log-odds of an event as a linear combination of one or more independent variables. In regression analysis, logistic regression (or logit regression)...

called regressors, predictors, covariates, explanatory variables or features). The most common form of regression analysis is linear regression, in which...

seen as generalizations of linear models (in particular, linear regression), although they can also extend to non-linear models. These models became...

Linear regression includes any approach to modelling a predictive relationship for one set of variables based on another set of variables, in such a way...

The general linear model or general multivariate regression model is a compact way of simultaneously writing several multiple linear regression models...

therefore is not cost-effective. The "predictive" component of predictive maintenance stems from the goal of predicting the future trend of the equipment's...

Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data...

Code-excited linear prediction (CELP) is a linear predictive speech coding algorithm originally proposed by Manfred R. Schroeder and Bishnu S. Atal in...

predictive power, simply reversing its decisions leads to a new predictive method C′ which has positive predictive power. When the C method predicts p...

simple linear regression). Bivariate analysis can be contrasted with univariate analysis in which only one variable is analysed. Like univariate analysis, bivariate...

Explained variation Linear trend estimation Mixed-design analysis of variance Multivariate analysis of covariance (MANCOVA) Permutational analysis of variance...

basic setup (the perceptron algorithm, support vector machines, linear discriminant analysis, etc.) is the procedure for determining (training) the optimal...

Runtime predictive analysis (or predictive analysis) is a runtime verification technique in computer science for detecting property violations in program...

In statistics, a proper linear model is a linear regression model in which the weights given to the predictor variables are chosen in such a way as to...

is a type of best linear unbiased prediction. The topic of spatial dependence is of importance to geostatistics and spatial analysis.[citation needed]...

Linear least squares (LLS) is the least squares approximation of linear functions to data. It is a set of formulations for solving statistical problems...

falsifying existing hypotheses. Predictive analytics focuses on the application of statistical models for predictive forecasting or classification, while...

University Press. ISBN 978-0-521-68567-2. Siegel, Eric (2013). Predictive Analysis: The Power to Predict Who Will Click, Buy, Lie, or Die. Hoboken, NJ: John Wiley...

1037/0003-066X.34.7.571. archived pdf Draper, David (1988). "Rank-Based Robust Analysis of Linear Models. I. Exposition and Review". Statistical Science. 3 (2): 239–257...