安裝中文字典英文字典辭典工具!
安裝中文字典英文字典辭典工具!
|
- Posterior Predictive Distributions in Bayesian Statistics - Physics Forums
Confessions of a moderate Bayesian, part 4 Bayesian statistics by and for non-statisticians Read part 1: How to Get Started with Bayesian Statistics Read part 2: Frequentist Probability vs Bayesian Probability Read part 3: How Bayesian Inference Works in the Context of Science Predictive distributions
- bayesian - Flat, conjugate, and hyper- priors. What are they? - Cross . . .
Today, Gelman argues against the automatic choice of non-informative priors, saying in Bayesian Data Analysis that the description "non-informative" reflects his attitude towards the prior, rather than any "special" mathematical features of the prior (Moreover, there was a question in the early literature of at what scale a prior is
- Bayesian vs frequentist Interpretations of Probability
Bayesian probability frames problems in e g statistics in quite a different way, which the other answers discuss The Bayesian system seems to be a direct application of the theory of probability, which seeks to avoid inferring anything which is not already known, and only inferring based on exactly what has been observed
- What is the best introductory Bayesian statistics textbook?
My bayesian-guru professor from Carnegie Mellon agrees with me on this having the minimum knowledge of statistics and R and Bugs(as the easy way to DO something with Bayesian stat) Doing Bayesian Data Analysis: A Tutorial with R and BUGS is an amazing start You can compare all offered books easily by their book cover!
- bayesian - Can someone explain the concept of exchangeability . . .
The concept is invoked in all sorts of places, and it is especially useful in Bayesian contexts because in those settings we have a prior distribution (our knowledge of the distribution of urns on the table) and we have a likelihood running around (a model which loosely represents the sampling procedure from a given, fixed, urn)
- bayesian - What is the difference between R hat and psrf . . . - Cross . . .
In convergence diagnosis in WinBUGS JAGS Stan, there are different statistics reported for each variable In WinBUGS Stan, Rhat ($\\hat{R}$) is reported In JAGS with the runjags package, psrf (Pote
- bayesian - Can somebody explain to me NUTS in english . . . - Cross Validated
The no U-turn bit is how proposals are generated HMC generates a hypothetical physical system: imagine a ball with a certain kinetic energy rolling around a landscape with valleys and hills (the analogy breaks down with more than 2 dimensions) defined by the posterior you want to sample from
- bayesian - What prior distributions could should be used for the . . .
In his widely cited paper Prior distributions for variance parameters in hierarchical models (916 citation so far on Google Scholar) Gelman proposes that good non-informative prior distributions for the variance in a hierarchical Bayesian model are the uniform distribution and the half t distribution If I understand things right this works
|
|
|