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Gamma 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-square distribution are special cases of the gamma distribution. There are two equivalent parameterizations in common use: 1. * With a shape parameter and a scale parameter . 2. * With a shape parameter and an inverse scale parameter , called a rate parameter. In each of these forms, both parameters are positive real numbers. The gamma distribution is the maximum entropy probability distribution (both with respect to a uniform base measure and a base measure) for a random variable for which E[X] = kθ = α/β is fixed and greater than zero, and E[ln(X)] = ψ(k) + ln(θ) = ψ(α) − ln(β) is fixed (ψ is the digamma function). (Wikipedia).

Gamma distribution
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39 - The gamma distribution - an introduction

This video provides an introduction to the gamma distribution: describing it mathematically, discussing example situations which can be modelled using a gamma in Bayesian inference, then going on to discuss how its two parameters affect the shape of the distribution intuitively, and finall

From playlist Bayesian statistics: a comprehensive course

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The Normal Distribution (1 of 3: Introductory definition)

More resources available at www.misterwootube.com

From playlist The Normal Distribution

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Number Theory 1.2 : The Gamma Function

In this video, I introduce the gamma function and show a few properties of it. Email : fematikaqna@gmail.com Code : https://github.com/Fematika/Animations Notes : None yet

From playlist Number Theory

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Multivariate Gaussian distributions

Properties of the multivariate Gaussian probability distribution

From playlist cs273a

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What is a Sampling Distribution?

Intro to sampling distributions. What is a sampling distribution? What is the mean of the sampling distribution of the mean? Check out my e-book, Sampling in Statistics, which covers everything you need to know to find samples with more than 20 different techniques: https://prof-essa.creat

From playlist Probability Distributions

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The Gamma Function for Half Integer Values

Help me create more free content! =) https://www.patreon.com/mathable Merch :v - https://teespring.com/de/stores/papaflammy https://www.amazon.com/shop/flammablemaths https://shop.spreadshirt.de/papaflammy Reflection Formula: https://www.youtube.com/wa

From playlist Number Theory

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The Normal Distribution

We use the Normal Distribution app on ArtofSat.com to show how to find probabilities and percentiles under the normal distribution. We also use the app to explain how the two parameters mu (the mean) and sigma (the standard deviation) determine the shape of the distribution.

From playlist Chapter 6: Distributions

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(ML 7.7.A1) Dirichlet distribution

Definition of the Dirichlet distribution, what it looks like, intuition for what the parameters control, and some statistics: mean, mode, and variance.

From playlist Machine Learning

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Lecture 2. Power law and scale-free networks.

Network Science 2021 @ HSE http://www.leonidzhukov.net/hse/2021/networks/

From playlist Network Science, 2021

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Samory Kpotufe: "Some New Insights On Transfer Learning"

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From playlist Machine Learning for Physics and the Physics of Learning 2019

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Some Recent Insights on Transfer Learning - Samory Kpotufe

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From playlist Mathematics

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27 - Prior predictive distribution: example Disease - 2

This video provides an example of deriving the prior predictive distribution (beta-binomial) for the case of a beta prior and a binomial likelihood. If you are interested in seeing more of the material on Bayesian statistics and inference, arranged into a playlist, please visit: https://w

From playlist Bayesian statistics: a comprehensive course

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The dynamical Φ43Φ34 model: derivation of the renormalised equations - Martin Hairer

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From playlist Mathematics

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27 - Prior predictive distribution: example Disease - 1

This video provides an example of deriving the prior predictive distribution (beta-binomial) for the case of a beta prior and a binomial likelihood. If you are interested in seeing more of the material, arranged into a playlist, please visit: https://www.youtube.com/playlist?list=PLFDbGp5

From playlist Bayesian statistics: a comprehensive course

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42 - Prior predictive distribution for Gamma prior to Poisson likelihood

This video provides a derivation of the prior predictive distribution - a negative binomial - for when there is a Gamma prior to a Poisson likelihood. If you are interested in seeing more of the material on Bayesian statistics, arranged into a playlist, please visit: https://www.youtube.

From playlist Bayesian statistics: a comprehensive course

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Petru Constantinescu - On the distribution of modular symbols and cohomology classes

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From playlist École d'Été 2022 - Cohomology Geometry and Explicit Number Theory

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Inverse normal with Z Table

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From playlist Unit 2: Normal Distributions

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Gamma process | Exponential family | Beta distribution | Moment (mathematics) | Poisson regression | Precision (statistics) | Inverse transform sampling | Conjugate prior | Dirichlet distribution | Mean | Shape parameter | Generalized inverse Gaussian distribution | Statistics | Exponential integral | Chi-squared distribution | Cumulative distribution function | Inverse-gamma distribution | Exponential distribution | Probability density function | Independent and identically distributed random variables | Rejection sampling | Sample mean | Infinite divisibility (probability) | Ramanujan theta function | Trigamma function | Weibull distribution | Generalized integer gamma distribution | Prior probability | Method of moments (statistics) | Bayesian statistics | Generalized gamma distribution | Digamma function | Mixture distribution | Statistical parameter | Pareto distribution | Poisson distribution | Laplace transform | Gompertz distribution | Maxwell–Boltzmann distribution | Scale parameter | Kullback–Leibler divergence | Laurent series | Variance | Half-normal distribution | Log–log plot | Gamma function | Rayleigh distribution | Closed-form expression | Integer | Matrix gamma distribution | Maximum entropy probability distribution | Incomplete gamma function | Probability distribution | Normal distribution | Exponential dispersion model | Natural exponential family | K-distribution | Negative binomial distribution | Random variable | Moment-generating function | Probability theory | Erlang distribution | Wishart distribution | Stable count distribution | Newton's method | Bayesian inference | Econometrics | Coefficient of variation | Tweedie distribution