bayesian inference

I've read quite a few posts comparing/contrasting bayesian and frequentist statistics. But there's one thing that I'm still struggling to understand. Based on the following premises (which I think are correct): Premise 1: A 'sampling distribution' of a statistic (e.g., a sample mean) is a piece...

Hi guys, I am doing a Bayesian updating for housing construction defects. But the observed data is very limited and incomplete. My model is beta binomial. beta (a1, a2) is my prior for defect rate for roof connections. The number of defects in n connections follow binomial (n, p), where p is...

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I need help with this Bayesian inference problem: Basketball team players are shooting balls in a game with the statistics of X = {(ki, ni)}. ki is the number of successful shots out of ni shots for each player. ki|ni,pi ~ Bin(ni,pi). The probabilities for score pi follows the connection pi ~...

-2 down vote favorite I cant get my head round the following exercise: You are testing dice for a casino to make sure that sixes do not come up more frequently than expected. Because you do not want to manually roll dice all day, you design a machine to roll a die repeatedly and record the...

I'm beginning to learn about Bayesian theory but I'm stumped on the ideal approach for combining multiple weighted inputs. Here's an example to make this more concrete. Let's say that I want to determine the probability that John will like a particular cookie. I know that generally John likes...

Hi guys, I am trying to set up a Bayesian Hierarchical model for customer spending, and was hoping to clarify a couple of things. I want to look at the returns on investment amongst people who buy our products for a particular marketing initiative. So what we have is: - A general customer base...

I have a "two-column" data set, with a multi-class categorical variable A, and two-class variable B. It is assumed that each observation is independent. For each category of variable A, I want to make a Bayesian estimate of a binomial parameter for class 1 of variable B, consistent with the...

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...

hello, actually i am new to statistics and i have to work with bayesian analysis.i need to use bayesian model to perform classification of hyperspectral images.i went through quite a few papers and have understood to some extent.but i wanted to know that do the gibbs sampling method and...

I believe that it is inappropriate to define prior distributions based on the same data you will be analyzing with those priors. In other words, the priors should not come from the **same** data set (i.e., from descriptive stats, etc) that you are about to estimate a model for. Does anyone...

I work as a Ph.D. student in structural bioinformatics, and build bayesian models for our data. It's been quite a while since I stumbled upon the problem I will expose, and it arises in a lot of cases in the modeling I do, regardless of the data source. I have the feeling it's due to my...