Bayesian inference is a method of statistical inference in which some kind of evidence or observations are used to calculate the probability that a hypothesis may be true, or else to update its previously-calculated probability.
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How to quantify a sequential hypothesis testing problem to conclude a certain experiment is better over the other, in a bayesian framework?
I am a newbie.
I have the following setup of a hypothetical experiment.
I have N places in a big building (think a huge palace) where I have kept 'N' different types of bird-food for birds.
Birds ...
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53 views
Simple cloud computing to run R + JAGS simulations
I want to simulate the frequentist properties of a Bayesian model. So, for example, I might want to fit a Bayesian model 1,000 times to 50 different configurations each of which takes about 10 seconds ...
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Bayesian inference over an unknown variance
I am observing a random variable $X \in \mathbb{R}$ which can be assumed to be normally distributed with mean $\mu$ and variance $\sigma^2$. I am interested in fitting a posterior distribution over ...
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Learning parameters of non-parametric Bayesian models
I have a sample of Chinese restaurant process which I want to model as Pitman–Yor process. How do I determine parameters of Pitman-Yor model from given sample?
For Dirichlet process I would just use ...
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29 views
Need help calculating a Bayes estimation for a Poisson
My study group and I are stuck on this Bayes' estimator problem.
The question is:
Let X~Pois($\lambda$)
Find the Bayes estimator for $\lambda$ with respect to:
(i) The prior distribution: ...
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26 views
Naive Bayes feature probabilities (Do I double count words?)
I'm prototyping my own Naive Bayes bag o' words model, and I had a question about calculating the feature probabilities.
Let's say I've got two classes, I'll just use spam and not-spam since that's ...
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38 views
How to do a Bayesian survival analysis and determine which variables are useful?
I can measure two variables on each patient in a survival study (I have the measurements and the survival times; some patients outlive the study and are therefore censored). I know that it is possible ...
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Java, Weka: How to predict numeric attribute? [migrated]
I was trying to use NaiveBayesUpdateable classifier from Weka. My data contains both nominal and numeric attributes:
...
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56 views
Under what conditions do Bayesian and frequentist point estimators coincide?
With a flat prior, the ML (frequentist -- maximum likelihood) and the MAP (Bayesian -- maximum a posteriori) estimators coincide.
More generally, however, I'm talking about point estimators derived ...
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72 views
Why is the Likelihood function NOT a case of the inverse fallacy?
This may be a trivial question, but as a research psychologist I do not have a robust statistics background to answer it.
It appears to me that the likelihood function--$L(\theta | \text{data}) = ...
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Bayesian uninformative priors vs. frequentist Null Hypotheses: what's the relationship?
I came across this image in a blog post here.
I was disappointed that reading the statement did not illicit the same facial expression for me as it did for this guy.
So, what is meant by the ...
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23 views
Updating Time-To-Event distribution given quantity of time elapsed with no event occurence
I'm trying to find a method to update a time to event distribution given the passage of time without the event occurring.
For example, if I am waiting for a bus and the time to arrival can be ...
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47 views
Degrees of freedom for Gaussian Process
I am reading this paper on Generalised Wishart Process (GWP). It is about modelling covariance matrix of D - dimensional gaussian processes (GP) as GWP. I fail to understand interpretation of "degrees ...
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33 views
Kalman- Bucy filter: prior mean change
I have a question on Kalman-Bucy filter:
the prior distribution is $g \sim N(0,σ_g^2 )$, signal is $ds=(μ+g_t )dt+σdZ_t$, posterior distribution becomes $g_t \sim N((\hat{g_t},\hatσ_t^2)$. ...
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66 views
Do Bayes factors require multiple comparison correction?
As the title: Do Bayes factors require mutliple comparion correction?
For more context, I am calculating very many likelihood ratio tests and I am thinking about how to handle multiple comparison ...
