Questions tagged [gamma-distribution]

A non-negative continuous probability distribution indexed by two strictly positive parameters.

If a variable $X$ follows a Gamma distribution with shape parameter $k > 0$ and scale parameter $\theta$, then it is a continuous random variable with probability density function:

$$ p(x) = \frac{1}{\theta^k}\frac{1}{\Gamma(k)}x^{k-1}e^{-\frac{x}{\theta}} $$

It follows that $\mathbb{E}(X) = k \theta$ and ${\rm var}(X) = k \theta^2$.

In some texts, the Gamma distribution is parameterized by the rate parameter $\beta$, instead of the scale parameter $\theta$, of which it is the reciprocal, in other words: $\beta = 1/\theta$.

The exponential distribution ($k=1$) and the $\chi^2$ distribution (with $\nu$ degrees of freedom, $k=\frac{\nu}{2}$, $\theta = 2$) are both special cases of the Gamma distribution.

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When to use gamma GLMs?

The gamma distribution can take on a pretty wide range of shapes, and given the link between the mean and the variance through its two parameters, it seems suited to dealing with heteroskedasticity in non-negative data, in a way that log-transformed…
generic_user
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Choosing between LM and GLM for a log-transformed response variable

I'm trying to understand the philosophy behind using a Generalized Linear Model (GLM) vs a Linear Model (LM). I've created an example data set below where: $$\log(y) = x + \varepsilon $$ The example does not have the error $\varepsilon$ as a…
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Which has the heavier tail, lognormal or gamma?

(This is based on a question that just came to me via email; I've added some context from a previous brief conversation with the same person.) Last year I was told that the gamma distribution is heavier tailed than the lognormal, and I've since been…
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Generic sum of Gamma random variables

I have read that the sum of Gamma random variables with the same scale parameter is another Gamma random variable. I've also seen the paper by Moschopoulos describing a method for the summation of a general set of Gamma random variables. I have…
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Gamma vs. lognormal distributions

I have an experimentally observed distribution that looks very similar to a gamma or lognormal distribution. I've read that the lognormal distribution is the maximum entropy probability distribution for a random variate $X$ for which the mean and…
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Good methods for density plots of non-negative variables in R?

plot(density(rexp(100)) Obviously all density to the left of zero represents bias. I'm looking to summarize some data for non-statisticians, and I want to avoid questions about why non-negative data has density to the left of zero. The plots are…
generic_user
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Real-life examples of common distributions

I am a grad student developing an interest for statistics. I like the material over-all, but I sometimes have a hard time thinking about applications to real life. Specifically, my question is about commonly used statistical distributions (normal -…
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The relationship between the gamma distribution and the normal distribution

I recently found it necessary to derive a pdf for the square of a normal random variable with mean 0. For whatever reason, I chose not to normalise the variance beforehand. If I did this correctly then this pdf is as follows: $$ N^2(x; \sigma^2) =…
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Sum of exponential random variables follows Gamma, confused by the parameters

I've learned sum of exponential random variables follows Gamma distribution. But everywhere I read the parametrization is different. For instance, Wiki describes the relationship, but don't say what their parameters actually mean? Shape, scale,…
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How to interpret parameters in GLM with family=Gamma

I have a question regarding parameter interpretation for a GLM with a gamma distributed dependent variable. This is what R returns for my GLM with a log-link: Call: glm(formula = income ~ height + age + educat + married + sex + language +…
Cajira
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Weibull Distribution v/s Gamma Distribution

What is the difference between the intuition behind Gamma and Weibull distributions? Is there any relationship between the two densities ? Kindly help.
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Construction of Dirichlet distribution with Gamma distribution

Let $X_1,\dots,X_{k+1}$ be mutually independent random variables, each having a gamma distribution with parameters $\alpha_i,i=1,2,\dots,k+1$ show that $Y_i=\frac{X_i}{X_1+\cdots+X_{k+1}},i=1,\dots,k$, have a joint ditribution as…
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Estimating gamma distribution parameters using sample mean and std

I'm trying to estimate the parameters of a gamma distribution that fits best to my data sample. I only want to use the mean, std (and hence variance) from the data sample, not the actual values - since these won't always be available in my…
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Is it possible to understand pareto/nbd model conceptually?

I am learning to use BTYD package that uses Pareto/NBD model to predict when will be a customer is expected to be back. However, all literature on this model is full of mathematics and there does not appear to be a simple/conceptual explanation of…
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Which diagnostics can validate the use of a particular family of GLM?

This seems so elementary, but I always get stuck at this point… Most of the data I deal with are non-normal, and most of the analyses based on a GLM structure. For my current analysis, I have a response variable that is "walking speed"…
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