Bayesian confidence interval, Advanced Statistics

Bayesian confidence interval: An interval of the posterior distribution which is so that the density of it at any point inside the interval is greater than that of the density at any point outside and that the area which comes under the curve for that interval is equal to the prespeci?ed probability level. For any probability level there is basically only one such interval, which is also often called as the highest posterior density area. Unlike the usual con?dence interval related with the frequentist inference, here the intervals state the range within which parameters lie with a certain probability. 

Posted Date: 7/26/2012 5:21:23 AM | Location : United States

Related Discussions:- Bayesian confidence interval, Assignment Help, Ask Question on Bayesian confidence interval, Get Answer, Expert's Help, Bayesian confidence interval Discussions

Write discussion on Bayesian confidence interval
Your posts are moderated
Related Questions
The process of providing the numerical value for the population parameter on the basis of information gathered from a sample. If a single ?gure is computed for the unknown paramete

i will like to submit my project for you to do on chi-square, ANOVA, and correlation and simple regression. how can we do this?

Hi , Im currently taking the course Financial Econometrics of Master of Finance at RMIT. I find it really difficult to understand the course''s material and now im having the majo

Auto correlation : The correlation of the internal observations in the time series, generally expressed as a function of the time lag between the observations. It is also used for

The GRE has a combined verbal and quantitative mean of 1000 and a standard deviation of 200.

K-means cluster analysis is the method of cluster analysis in which from an initial partition of observations into K clusters, each observation in turn is analysed and reassigned,

Latent class analysis is a technique of assessing whether the set of observations including q categorical variables, in specific, binary variables, consists of the number of diffe

Difference between tretment design and experimental design

The functions of the data and the parameters of interest which can be brought in use to conduct inference about the parameters when full distribution of the observations is unknown