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Results tagged with bayesian
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user 109101
Bayesian inference is a method of statistical inference that relies on treating the model parameters as random variables and applying Bayes' theorem to deduce subjective probability statements about the parameters or hypotheses, conditional on the observed dataset.
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The gradient vector in Hamiltonian Monte Carlo (leapfrog method)
Let $x_{t}, \omega_{t} \in \mathbb{R^{d}}$
The Hamiltonian Monte Carlo says this:
Deterministic: it relies on the Hamiltonian dynamics so given an initial state, at any time $t$, specified by the pos …
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why does posterior prediction involve integration over all parameter space?
The primary objective of Bayesian inference is to compute the posterior. …
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Bayes rule and conditional - marginal factorisation (joint posterior)
I have some confusion regarding Bayes rule for joint posterior (I think primarily due to the context in which notations are used)
Let $P(\theta_{1}, \theta_{2} | X)$ be a joint posterior over the para …
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Probability that event one and event occurring simultaneously
The sample space for different ratings of food is given in the table below:
For the rating by two person, what is the probability that one of the two will rate the meal as excellent and the other w …
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Metropolis - Hastings sampling: histogram shapes looks sane but bin values are off
The target distribution is of the form:
$ p(x) = x^{-6}.e^{\frac{-2.475}{x}}$ with a support in the interval $[0.0, 2.0]$.
This gives a plot like
Now, to choose a proposal kernel, I think a lognormal …
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