### Some articles on *prior distribution, priors, prior, distributions, distribution*:

Hyperprior

... In Bayesian statistics, a hyperprior is a

... In Bayesian statistics, a hyperprior is a

**prior distribution**on a hyperparameter, that is, on a parameter of a**prior distribution**... the use of hyper is to distinguish it from a**prior distribution**of a parameter of the model for the underlying system ... They arise particularly in the use of conjugate**priors**...Doomsday Argument - Variations - Gott's Formulation: 'vague Prior' Total Population

... Gott specifically proposes the functional form for the

... Gott specifically proposes the functional form for the

**prior distribution**of the number of people who will ever be born (N) ... Gott's DA used the vague**prior distribution**... where P(N) is the probability**prior**to discovering n, the total number of humans who have yet been born ...Approximate Bayesian Computation - Pitfalls and Remedies - General Risks in Statistical Inference Exacerbated in ABC -

... The specification of the range and the

**Prior Distribution**and Parameter Ranges... The specification of the range and the

**prior distribution**of parameters strongly benefits from previous knowledge about the properties of the system ... One criticism has been that in some studies the “parameter ranges and**distributions**are only guessed based upon the subjective opinion of the investigators”, which is connected to classical objections of ... However, theoretical results regarding objective**priors**are available, which may for example be based on the principle of indifference or the principle of maximum ...Hidden Markov Model - Extensions

... themselves can either be discrete (typically generated from a categorical

... themselves can either be discrete (typically generated from a categorical

**distribution**) or continuous (typically from a Gaussian**distribution**) ... all hidden and observed variables follow a Gaussian**distribution**... Hidden Markov models are generative models, in which the joint**distribution**of observations and hidden states, or equivalently both the**prior distribution**of hidden states (the transition probabilities) and ...Categorical Distribution - With A Conjugate Prior

... In Bayesian statistics, the Dirichlet

... In Bayesian statistics, the Dirichlet

**distribution**is the conjugate**prior distribution**of the categorical**distribution**(and also the multinomial**distribution**) ... This means that in a model consisting of a data point having a categorical**distribution**with unknown parameter vector p, and (in standard Bayesian style) we choose to treat this parameter as a ... such a case, starting from what we know about the parameter**prior**to observing the data point, we then can update our knowledge based on the data point and end up with a new**distribution**of the same form as the old one ...### Famous quotes containing the words distribution and/or prior:

“Classical and romantic: private language of a family quarrel, a dead dispute over the *distribution* of emphasis between man and nature.”

—Cyril Connolly (1903–1974)

“They never taste who always drink;

They always talk who never think.”

—Matthew *Prior* (1664–1721)

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