bayesian

I know that if the prior distribution is chosen to be a continuous uniform distribution, then the exact posterior distribution will simply the normalized version of the likelihood function. I was wondering how i would write this out as a proof?

I have noticed a trend with hiring managers to vault candidates that are well versed in Bayesian analysis to the top. This is not necessarily because someone will sink or swim based on their allegiance to Bayes, these managers may not even have implemented any of the methodology at all yet...

I've used python to analyse data from AB tests using Bayesian analysis, and for all tests I assume no prior knowledge and so set alpha = beta = 1. However I'm finding some odd results at low data volumes, which I thought was my code, but I'm also seeing here...

it's a actually an informatics math related question. But i want to start here to get a first opinion. As a software engineer and cryptographer, I'm developing an application to predict to price of certain alt-coin. I have read a paper about the math behind the algorithm. I have a more then...

Hi you’ll, I have a thought problem that might not have an easy/correct answer. It looks to be a Bayesian at first glance – and it might be – but because I am using some complicated machine-learning algorithms, and because of the nature of the problem, the water are muddy for me. I am just...

Let's say we have a multimomial logit problem and we find the best beta coeffcients b* aggregating all units. The inverse of the Hessian at b* gives us a VCV matrix at this point which shows roughly how betas vary across units. The other way to get a VCV matrix is to use Hierarchical Bayes where...

Description I have three separate test I perform over the course of an interview. At the end of the interview the tests analyze their respective data and spit out an assessment that says the person being interviewed was excited by the interview or annoyed by the interview along with a...

dear all members i have a small problem in the code below. in the last step gen initial and after press on this key i cannot get on result because the program still generate these values and i cannot get on any resutls after then i must close the program because it is not work and restart it...

If you have 2 parameters a and b and a observed data set x, and wish to calculate the posterior distribution of a given b is the following true P(a|b,x) proportional to P(a,b| x) Where proportionality is in a. I had wrote this down somewhere but can't remember why or if it is right...

Hi guys! So okay this week in class we started learning about Gibbs sampling and full conditional probabilities. I seemed to understand all the examples in class on how to derive full conditional probabilities, but got to the hw and was completely lost. I feel that the reason for this is that...

I'm trying to sample from a posterior (with 50 dimensions) and I've got a proposal distribution which gives a overall acceptance rate of 0.3. However when I take 20000 draws, there are a couple occasions where the proposal is rejected 500-1000 times consecutively. I haven't much experience in...

Hi, I have 10 prior distributions one for each of theta1, theta2..... . The prior distribution for theta1 is Gamma(a1,b1), and the others are described similarly. Now I have an observation x, where X~Poisson(theta1 +theta2). I would like to get separate posterior distribution for theta1...

Hello, I am attempting to use AMOS to run a number of structural equation models. Several of my manifest variables are ordered categorical, a few (intended to be exogenous) are even binary. Unfortunately I only have access to secondary summary data (i.e. a covariance matrix with means and...

I'm working on a problem on my own (not for class or work) and I just wanted to get some outside opinions before I progress further. As far as my background, I've taken some introductory statistics courses for psychology majors, and an intro probability and statistics course for engineers...

Hi, I need to compare four different models (logistic regression), model selection is performed using bayes factors using the BIC statisic. BIC can be transformed to the probability of the data given a model: PrBIC(D|Hi) = exp[-BIC(Hi)/2] And so, we can compute the Bayes factors...

Background: I'm currently trying to learn how to use Bayesian Analysis for split testing two sets of binomial data. (Web analytics, Multi-Armed Bandit approach, etc). The Beta distribution kept coming up in this research, so Im trying to understand and apply it better. So, the best...

Hi All First time here and its been a long time since I studied probability...was hoping someone could assist in the interpretation of some data I have gathered. From some customer and historical contact data I am trying to tell a story along the lines of 'customers who are contacted are...

Hi folks: I'm trying to apply cross-validation of models (e.g. the paper "On Cross-Validation of Bayesian Models" by Alqallaf and Gustafson) in the context of count data and have run into an interesting problem. My understanding of how such cross-validation should work is that one draws...

So, I foolishly tried to implement a test Gelman and his colleagues propose to determine whether observed data actually fits a model (Bayesian Data Analysis, Edition 1, p.172; or better: Gelman, Meng, Stern, 1996). If the test worked as advertised, it would be really useful--an omnibus way to...