Bayesian linear regression is a type of conditional modeling in which the mean of one variable is described by a linear combination of other variables...
18 KB (3,233 words) - 10:15, 10 April 2025
In statistics, Bayesian multivariate linear regression is a Bayesian approach to multivariate linear regression, i.e. linear regression where the predicted...
15 KB (2,737 words) - 18:42, 29 January 2025
involving multivariate data, for example simple linear regression and multiple regression, are not usually considered to be special cases of multivariate statistics...
18 KB (2,015 words) - 08:53, 9 June 2025
general linear model or general multivariate regression model is a compact way of simultaneously writing several multiple linear regression models. In...
12 KB (1,213 words) - 14:19, 3 June 2025
explanatory variables is a multiple linear regression. This term is distinct from multivariate linear regression, which predicts multiple correlated dependent...
76 KB (10,482 words) - 04:54, 7 July 2025
including Bayesian regression and least squares fitting to variance stabilized responses, have been developed. Ordinary linear regression predicts the...
31 KB (4,231 words) - 04:22, 20 April 2025
non-linear models (e.g., nonparametric regression). Regression analysis is primarily used for two conceptually distinct purposes. First, regression analysis...
37 KB (5,235 words) - 03:23, 20 June 2025
In statistics, multivariate adaptive regression splines (MARS) is a form of regression analysis introduced by Jerome H. Friedman in 1991. It is a non-parametric...
18 KB (2,701 words) - 08:55, 1 July 2025
linear model for non-normal distributions Bayesian linear regression, where statistical analysis is from a Bayesian viewpoint Bayesian multivariate linear...
1 KB (163 words) - 06:57, 22 August 2015
distributed if every linear combination of its k components has a univariate normal distribution. Its importance derives mainly from the multivariate central limit...
65 KB (9,594 words) - 15:19, 3 May 2025
sampling Bayesian information criterion Bayesian linear regression Bayesian model comparison – see Bayes factor Bayesian multivariate linear regression Bayesian...
87 KB (8,280 words) - 23:04, 12 March 2025
function. Linear regression is a restricted case of nonparametric regression where m ( x ) {\displaystyle m(x)} is assumed to be a linear function of...
7 KB (677 words) - 05:52, 7 July 2025
List of things named after Thomas Bayes (redirect from Bayesian)
descriptions of redirect targets Bayesian multivariate linear regression – Bayesian approach to multivariate linear regression Bayesian Nash equilibrium – Game...
6 KB (965 words) - 14:43, 23 August 2024
Quantile regression is an extension of linear regression used when the conditions of linear regression are not met. One advantage of quantile regression relative...
29 KB (4,109 words) - 04:27, 20 June 2025
Machine learning (section Bayesian networks)
variables to higher-dimensional space. Multivariate linear regression extends the concept of linear regression to handle multiple dependent variables...
140 KB (15,571 words) - 08:04, 6 July 2025
In statistics, the Bayesian information criterion (BIC) or Schwarz information criterion (also SIC, SBC, SBIC) is a criterion for model selection among...
12 KB (1,674 words) - 23:49, 17 April 2025
Empirical Bayes method (redirect from Empirical Bayesian)
model, as well specific models for Bayesian linear regression (see below) and Bayesian multivariate linear regression. More advanced approaches include...
17 KB (2,643 words) - 23:42, 27 June 2025
the probit regression, (ii) threshold regression, (iii) smooth regression, (iv) logistic link regression, (v) Box–Cox transformed regressors ( m ( x ,...
28 KB (4,539 words) - 08:58, 21 March 2025
Gaussian process (redirect from Bayesian Kernel Ridge Regression)
distribution over functions in Bayesian inference. Given any set of N points in the desired domain of your functions, take a multivariate Gaussian whose covariance...
44 KB (5,929 words) - 11:10, 3 April 2025
Segmented linear regression is segmented regression whereby the relations in the intervals are obtained by linear regression. Segmented linear regression with...
11 KB (1,430 words) - 09:04, 31 December 2024
Poisson regression is a generalized linear model form of regression analysis used to model count data and contingency tables. Poisson regression assumes...
18 KB (2,750 words) - 19:37, 4 July 2025
estimators when linear regression models have some multicollinear (highly correlated) independent variables—by creating a ridge regression estimator (RR)...
31 KB (4,148 words) - 18:20, 3 July 2025
In statistics, simple linear regression (SLR) is a linear regression model with a single explanatory variable. That is, it concerns two-dimensional sample...
32 KB (5,331 words) - 19:00, 25 April 2025
categorical dependent variable (i.e. the class label). Logistic regression and probit regression are more similar to LDA than ANOVA is, as they also explain...
47 KB (6,037 words) - 16:42, 16 June 2025
Ordinary least squares (redirect from Ordinary least squares regression)
especially in the case of a simple linear regression, in which there is a single regressor on the right side of the regression equation. The OLS estimator is...
65 KB (9,098 words) - 10:14, 3 June 2025
an event as a linear combination of one or more independent variables. In regression analysis, logistic regression (or logit regression) estimates the...
127 KB (20,641 words) - 09:18, 24 June 2025
Naive Bayes classifier (redirect from Naive Bayesian classifier)
Anti-spam techniques Bayes classifier Bayesian network Bayesian poisoning Email filtering Linear classifier Logistic regression Markovian discrimination Mozilla...
50 KB (7,362 words) - 20:42, 29 May 2025
Errors and residuals (redirect from Errors and residuals in regression)
distinction is most important in regression analysis, where the concepts are sometimes called the regression errors and regression residuals and where they lead...
16 KB (2,164 words) - 16:12, 23 May 2025
variables whose linear combination follows a multivariate normal distribution, multivariate variance-covariance matrix homogeneity, and linear relationship...
11 KB (1,274 words) - 23:33, 23 June 2025
Normality test (section Bayesian tests)
Rogers-Stewart. One application of normality tests is to the residuals from a linear regression model. If they are not normally distributed, the residuals should...
12 KB (1,627 words) - 12:37, 9 June 2025