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Results tagged with bayesian
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user 174349
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.
1
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In Bayesian statistics does posterior probability become prior probability when new observat...
Just one thing, prior is a probability distribution, not a value like 50% (prior may be also improper.)
As an example with the Binomial and Beta prior:
Starting with a prior distribution $Be(1,1)$ …
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1
vote
How is MCMC relevant for Bayesian inference?
At each step of a Bayesian procedure you may need to normalize the product of the likelihood times the prior by computing an integral.
Example of a basic integration of x^2 in the interval [5,12]. …
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1
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Bayes' theorem applied to a binomial variable
You start using an Uniform prior, equivalent to a $Be(1,1)$. This two 1's can be understood as pseudo observations of "previous" experiments, let's say, having obtained 1 Yes, 1 No previously.
Now let …
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0
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Sequential Bayesian estimation of binary outcome
That is not a bayesian approach. … If you want to know the parameter p of a Bernouilli distribution, in the Bayesian approach, you start with a distribution of this parameter p, called the prior distribution. …
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14
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Is the mean of samples still a valid sample?
No, it is only valid in cases as the Cauchy distribution, the means of samples of the Cauchy follow the same Cauchy dstribution.
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