Template:Infobox probability distribution
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Example
Script error: No such module "infobox3cols". e^{-\frac{1}{2}\left(\frac{x - \mu}{\sigma}\right)^2}</math>
| cdf = <math>\frac{1}{2}\left[1 + \operatorname{erf}\left( \frac{x-\mu}{\sigma\sqrt{2}}\right)\right] </math> | quantile = <math>\mu+\sigma\sqrt{2} \operatorname{erf}^{-1}(2p-1)</math> | mean = <math>\mu</math> | median = <math>\mu</math> | mode = <math>\mu</math> | variance = <math>\sigma^2</math> | mad = <math>\sigma\sqrt{2/\pi}</math> | skewness = <math>0</math> | kurtosis = <math>0</math> | entropy = <math>\frac{1}{2} \log(2\pi e\sigma^2)</math> | mgf = <math>\exp(\mu t + \sigma^2t^2/2)</math> | char = <math>\exp(i\mu t - \sigma^2 t^2/2)</math> | fisher = <math>\mathcal{I}(\mu,\sigma) =\begin {pmatrix} 1/\sigma^2 & 0 \\ 0 & 2/\sigma^2\end{pmatrix}</math>
<math>\mathcal{I}(\mu,\sigma^2) =\begin {pmatrix} 1/\sigma^2 & 0 \\ 0 & 1/(2\sigma^4)\end{pmatrix}</math>
| KLDiv = <math>{ 1 \over 2 } \left\{ \left( \frac{\sigma_0}{\sigma_1} \right)^2 + \frac{(\mu_1 - \mu_0)^2}{\sigma_1^2} - 1 + 2 \ln {\sigma_1 \over \sigma_0} \right\}</math>
}}
Usage
The Template:Infobox probability distribution generates a right-hand side infobox, based on the specified parameters. To use this template, copy the following code in your article and fill in as appropriate:
{{Infobox probability distribution | name = | type = | pdf_image = | cdf_image = | notation = | parameters = | support = | pdf = | cdf = | quantile = | mean = | median = | mode = | variance = | mad = | skewness = | kurtosis = | entropy = | cross_entropy = | mgf = | cf = | pgf = | fisher = | moments = | KLdiv = | JSDiv = }}
Parameters
|name=
— Name at the top of the infobox; should be the name of the distribution without the word "distribution" in it, e.g. "Normal", "Exponential" (optional)|type=
— possible values are "discrete" (or "mass"), "continuous" (or "density"), and "multivariate"|pdf_image=
— probability density image-spec, such as:xxx.svg
.|pdf_caption=
— probability density image caption|pdf_image_alt=
— alternative text for the image in|pdf_image=
|cdf_image=
— cumulative distribution image-spec, such as:yyy.svg
.|cdf_caption=
— cumulative distribution image caption|cdf_image_alt=
— alternative text for the image in|cdf_image=
|notation=
— typical designation for this distribution, for example <math>\mathcal{N}(\mu,\sigma^2)</math>. The notation should include all the distribution parameters explained in the next cell.|parameters=
— parameters of the distribution family (such as μ and σ2 for the normal distribution).|support=
— the support of the distribution, which may depend on the parameters. Specify this as <syntaxhighlight lang="tex" inline><math>x \in some set</math></syntaxhighlight> for continuous distributions, and as <syntaxhighlight lang="tex" inline><math>k \in some set</math></syntaxhighlight> for discrete distributions.|pdf=
— probability density function (or probability mass function), such as: <syntaxhighlight lang="tex" inline><math>\frac{\Gamma(r+k)}{k!\Gamma(r)}p^r(1-p)^k</math></syntaxhighlight>. Please exclude the function label, such as "ƒ(x; μ,σ2)".|cdf=
— cumulative distribution function, e.g.:<math>I_p(r,k+1)\text{ where }I_p(x,y)</math> is the [[regularized incomplete beta function]]
.|quantile=
— quantile function (or inverse cumulative distribution function). If <math>F()</math> is the CDF and <math>Q()</math> is the quantile function, then <math>Q(F(x))=x</math>|mean=
— the mean, or expected value.|median=
— the median, only for univariate distributions.|mode=
— the mode.|variance=
— variance of the distribution, or covariance matrix in multivariate case.|mad=
— the mean absolute deviation.|skewness=
— the skewness.|kurtosis=
— the kurtosis excess.|entropy=
— the differential information entropy, preferably expressed in unspecified units using base-unspecific log(.) rather than base-specific ln(.) which yields entropy in units of nats only.|cross_entropy=
— the Cross entropy of the model|mgf=
— the moment-generating function, for example: <syntaxhighlight lang="tex" inline><math>\left(\frac{p}{1-(1-p) e^t}\right)^r</math></syntaxhighlight>.|char=
/|cf=
— the characteristic function, such as: <syntaxhighlight lang="tex" inline><math>\left(\frac{p}{1-(1-p) e^{it}}\right)^r</math></syntaxhighlight>.|pgf=
- the Probability-generating function.|fisher=
— the Fisher information matrix for the model.|KLDiv=
— the Kullback-Leibler divergence of the model|JSDiv=
— the Jensen-Shannon divergence of the model|moments=
— formulas to use in Method of moments for the model.|intro=
— optional message which will be displayed before all other content in the infobox.|marginleft=
— margin space left of infobox (default: 1em).|box_width=
— width of the infobox (default: 325px).
|parameters2=
, |support2=
, |pdf2=
, |cdf2=
, |mean2=
, |median2=
, |mode2=
, |variance2=
, |mad=
, |skewness2=
, |kurtosis2=
, |entropy2=
, |mgf2=
, |char2=
/|cf2=
, |moments2=
, |fisher2=
are the same as their counterparts above. They should be used when the distribution needs two sets to describe it, e.g. Gamma distribution.