Gaussian markov random field, Advanced Statistics

It is the multivariate normal random vector which satisfies certain conditional independence suppositions. This can be viewed as a model framework which contains a wide range of statistical models, together with models for time-series, images, longitudinal data, spatiotemporal processes, and the graphical models.

Posted Date: 7/28/2012 3:47:41 AM | Location : United States







Related Discussions:- Gaussian markov random field, Assignment Help, Ask Question on Gaussian markov random field, Get Answer, Expert's Help, Gaussian markov random field Discussions

Write discussion on Gaussian markov random field
Your posts are moderated
Related Questions
Cochrane collaboration : An international network of the individuals committed to preparing , maintaining and disseminating the systematic reviews of the effects of the health care

The Null Hypothesis - H0:  There is no heteroscedasticity i.e. β 1 = 0 The Alternative Hypothesis - H1:  There is heteroscedasticity i.e. β 1 0 Reject H0 if Q = ESS/2  >

Cohort component method : A broadly used method or technique of forecasting the age- and sex-speci?c population to the upcoming years, in which the initial population is strati?ed

Modern hotels and certain establishments make use of an electronic door lock system. To open a door an electronic card is inserted into a slot. A green light indicates that the doo

Item-total correlation is an  extensively used method for checking the homogeneity of the scale made up of number of items. It is simply the Pearson's product moment correlation c

Interim analyses : An analysis made before the planned end of a clinical trial, typically with the aim of detecting the treatment differences at the early stage and thus preventing

Laplace distribution : The probability distribution, f(x), given by the following formula   Can be derived as the distribution of the difference of two independent random var

The model for data containing continuous and categorical variables both.The categorical data are summarized by the contingency table and their marginal distribution, 182by the mult

Categorical variable : A variable which provides the appropriate label of observation after the allocation to one of the several possible categories, for instance, the respiratory

Lancaster models : The means of representing the joint distribution of the set of variables in terms of the marginal distributions, supposing all the interactions higher than a par