Bayesian Linear Regression

Bayesian Linear Regression

Regression analysis
  • Generalized linear model
  • Discrete choice
  • Logistic regression
  • Multinomial logit
  • Mixed logit
  • Probit
  • Multinomial probit
  • Ordered logit
  • Ordered probit
  • Poisson
  • Multilevel model
  • Fixed effects
  • Random effects
  • Mixed model
  • Nonlinear regression
  • Nonparametric
  • Semiparametric
  • Robust
  • Quantile
  • Isotonic
  • Principal components
  • Least angle
  • Local
  • Segmented
  • Errors-in-variables
  • Least squares
  • Ordinary least squares
  • Linear (math)
  • Partial
  • Total
  • Generalized
  • Weighted
  • Non-linear
  • Iteratively reweighted
  • Ridge regression
  • Least absolute deviations
  • Bayesian
  • Bayesian multivariate
  • Regression model validation
  • Mean and predicted response
  • Errors and residuals
  • Goodness of fit
  • Studentized residual
  • Gauss–Markov theorem

In statistics, Bayesian linear regression is an approach to linear regression in which the statistical analysis is undertaken within the context of Bayesian inference. When the regression model has errors that have a normal distribution, and if a particular form of prior distribution is assumed, explicit results are available for the posterior probability distributions of the model's parameters.

Read more about Bayesian Linear Regression:  Model Setup, Other Cases

Other articles related to "linear regression, linear, regression, bayesian linear regression, bayesian":

Introduction To Linear Regression - Assumptions
... Standard linear regression models with standard estimation techniques make a number of assumptions about the predictor variables, the response variables ... following are the major assumptions made by standard linear regression models with standard estimation techniques (e.g ... This means that the mean of the response variable is a linear combination of the parameters (regression coefficients) and the predictor variables ...
Bayesian Linear Regression - Other Cases
... the posterior by an approximate Bayesian inference method such as Monte Carlo sampling or variational Bayes ... The special case is called ridge regression ... analysis can be performed for the general case of the multivariate regression and part of this provides for Bayesian estimation of covariance matrices see Bayesian multivariate linear ...
Linear Functional - Examples and Applications - Integration
... Linear functionals first appeared in functional analysis, the study of vector spaces of functions ... A typical example of a linear functional is integration the linear transformation defined by the Riemann integral is a linear functional from the vector space C of continuous functions on ...
Visualizing Linear Functionals
... In finite dimensions, a linear functional can be visualized in terms of its level sets ... In three dimensions, the level sets of a linear functional are a family of mutually parallel planes in higher dimensions, they are parallel hyperplanes ... This method of visualizing linear functionals is sometimes introduced in general relativity texts, such as Gravitation by Misner, Thorne Wheeler (1973) ...
... A gyrator is a passive, linear, lossless, two-port electrical network element proposed in 1948 by Bernard D ... Tellegen as a hypothetical fifth linear element after the resistor, capacitor, inductor and ideal transformer ... Although the gyrator was conceived as a fifth linear element, its adoption makes both the ideal transformer and either the capacitor or inductor redundant ...