2. Find the mode of the
a. Beta distribution
b. Gamma distribution
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In probability theory and statistics, the beta distribution is a family of continuous ... For example, the beta distribution can be used in Bayesian analysis to describe initial knowledge
For example, the beta distribution can be used in ... To find the value of the Gamma function at other points we deduce an interesting ...
For example, the beta distribution can be used in ... To find the value of the Gamma function at other points we deduce an interesting ...
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distribution is a family of continuous probability distributions defined on the interval [0, 1] parametrized by two positive shape parameters, denoted by α and β, that appear as exponents of the random variable and control the shape of the distribution. It is a special case of the Dirichlet distribution.
In probability theory and statistics, the gamma distribution is a two-parameter family of continuous probability distributions. The exponential distribution, Erlang distribution, and chi-squared distribution are special cases of the gamma distribution. There are three different parametrizations in common use:
With a shape parameter k and a scale parameter θ.With a shape parameter α = k and an inverse scale parameter β = 1/θ, called a rate parameter.With a shape parameter k and a mean parameter μ = kθ = α/β.
In probability theory and statistics, the gamma distribution is a two-parameter family of continuous probability distributions. The exponential distribution, Erlang distribution, and chi-squared distribution are special cases of the gamma distribution. There are three different parametrizations in common use:
With a shape parameter k and a scale parameter θ.With a shape parameter α = k and an inverse scale parameter β = 1/θ, called a rate parameter.With a shape parameter k and a mean parameter μ = kθ = α/β.
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