# Tagged Questions

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### regarding conditional independence and its graphical representation

When studying covariance selection, I once read the following example. With respect to the following model: Its covariance and inverse covariance matrix are given as follows, I do not understand ...
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### Combining posterior probabilities from multiple classifiers

I am new to machine learning and can't get my head around this problem. I have two patient datasets, the first ($D_1$) contains $Y,Z,X$ that convey blood-sample information and the second ($D_2$) ...
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### Finding the full conditonal distribution when there are multiple distributions involved

6 neighboring countries have the following disease instances: $y = (y_1, y_2,...,y_n)$ with a population of $x = (x_1, x_2,...,x_n)$. The following model and prior distributions are considered: ...
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### Finding Jeffreys prior for the multivariate normal distribution. Conditional probability algebra

For the multivariate normal model, find Jeffrey's prior of the form $p_j(\theta, \Sigma|y1,...,yn)$, $p_j(\theta|\Sigma, y_1,...,y_n)$, and $p_j(\Sigma|y_1,...,y_n)$. Attempt: I know that ...
120 views

### Locomotive problem with various size companies

I'm working through Think Bayes (free here: http://www.greenteapress.com/thinkbayes/) and I'm on exercise 3.1. Here's a summary of the problem: "A railroad numbers its locomotives in order 1..N. One ...
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### Independence test

I'm working on Bayesian Network and I need to find a broad range of statistical test for testing independence and conditional independence between 2 variables with a potential conditioning set of ...
106 views

### How do programs like BUGS/JAGS automatically determine conditional distributions for Gibbs sampling?

Seems like full conditionals are often quite difficult to derive, yet programs like JAGS and BUGS derive them automatically. Can someone explain how they algorithmically generate full conditionals for ...
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212 views

### Bayes' Theorem - Probability Pants problem

I'm having an issue with a question regarding Bayes' Theorem. Here is the question: An online clothing store carries three brands of jeans. 40% of sales are brand A, 20% are brand B and the ...
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### Constructing a model from multiple non-independent and unreliable predictors?

I have an interesting modelling problem in which I am trying to forecast the occurrence of a type of weather event using an empirical model driven by measurements of a number of different physical ...
300 views

### Confidence intervals when using Bayes' theorem

I'm computing some conditional probabilities, and associated 95% confidence intervals. For many of my cases, I have straightforward counts of x successes out of ...
153 views

### Is Perkins et al.'s “skill score” an application of Bayes' theorem?

Perkins et al. (2007) introduce a "skill score" for measuring climate model output against observations. The score basically consists of measuring the overlap between probability density functions of ...
636 views

### How to calculate joint probabilities from conditional probabilities in a Bayesian Network?

This question is about Bayesian Networks. I want to calculate the probability for certain events to be in a certain state knowing all conditional probabilities. Consider that I am totally new to ...
106 views

### Time-wise treatment effect / survival analysis

Let's say I have some kind of survival data - i.e. I'm giving a drug that may cause mortality. So I have three patients: A, B and C. All are given the drug at Time t1. Let's say patient A dies at ...
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### Confused about relevance of Bayes' theorem to my problem

I've spent the morning teaching myself about Bayes's theorem, because I assumed that it was required to help me solve my problem. However, the answer I've ended up with is the same as I would have got ...
732 views

### Derive P(C | A+B) from Cox's two rules

I am working my way (self-study) through E.T. Jaynes' book Probability Theory - The Logic of Science Original Problem Exercise 2.1 says: "Is it possible to find a general formula for $p(C|A+B)$ ...
132 views

### What techniques are used for empirical, stochastic simulation of a time series?

Suppose you have recorded a set of paths in the $y,t$ plane, with $y = f(t)$, $f$ is a stochastic function (i.e. there is a noise term), and $t$ might be time or some other monotonic increasing ...
580 views

### How to calculate conditional & marginal probability for both the positive and negative hypotheses?

Sorry to keep bothering you guys with this thing, but another stupid question: Given the following data (from my previous question), how would one calculate the conditional probability and marginal ...
2k views

### Bayesian probability > 1 — is it possible?

Running a crude model using Bayesian inference, I get some results > 1 (ie, more than 100% "certain") for some combinations of "evidence". For instance, for one bit of evidence the conditional ...
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### Bayes Network computing conditional probabilities

There is a bayesian network Asia: I am computing based on ...