From Jason Turner

[rand.dist.norm]

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tmp/tmpp54fs68k/{from.md → to.md} RENAMED
@@ -1,20 +1,13 @@
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  #### Normal distributions <a id="rand.dist.norm">[[rand.dist.norm]]</a>
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  ##### Class template `normal_distribution` <a id="rand.dist.norm.normal">[[rand.dist.norm.normal]]</a>
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  A `normal_distribution` random number distribution produces random
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- numbers x distributed according to the probability density function $$%
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- p(x\,|\,\mu,\sigma)
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- = \frac{1}{\sigma \sqrt{2\pi}}
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- \cdot
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- % e^{-(x-\mu)^2 / (2\sigma^2)}
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- \exp{\left(- \, \frac{(x - \mu)^2}
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- {2 \sigma^2}
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- \right)
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- }
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- \text{ .}$$ The distribution parameters μ and σ are also known as this
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  distribution’s *mean* and *standard deviation*.
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  ``` cpp
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  namespace std {
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  template<class RealType = double>
@@ -83,13 +76,11 @@ constructed.
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  ##### Class template `lognormal_distribution` <a id="rand.dist.norm.lognormal">[[rand.dist.norm.lognormal]]</a>
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  A `lognormal_distribution` random number distribution produces random
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  numbers x > 0 distributed according to the probability density function
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- $$p(x\,|\,m,s) = \frac{1}{s x \sqrt{2 \pi}}
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- \cdot \exp{\left(-\frac{(\ln{x} - m)^2}{2 s^2}\right)}
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- \text{ .}$$
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  ``` cpp
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  namespace std {
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  template<class RealType = double>
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  class lognormal_distribution {
@@ -157,11 +148,11 @@ constructed.
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  ##### Class template `chi_squared_distribution` <a id="rand.dist.norm.chisq">[[rand.dist.norm.chisq]]</a>
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  A `chi_squared_distribution` random number distribution produces random
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  numbers x > 0 distributed according to the probability density function
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- $$p(x\,|\,n) = \frac{x^{(n/2)-1} \cdot e^{-x/2}}{\Gamma(n/2) \cdot 2^{n/2}} \text{ .}$$
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  ``` cpp
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  namespace std {
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  template<class RealType = double>
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  class chi_squared_distribution {
@@ -219,12 +210,11 @@ RealType n() const;
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  constructed.
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  ##### Class template `cauchy_distribution` <a id="rand.dist.norm.cauchy">[[rand.dist.norm.cauchy]]</a>
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  A `cauchy_distribution` random number distribution produces random
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- numbers x distributed according to the probability density function
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- $$p(x\,|\,a,b) = \left(\pi b \left(1 + \left(\frac{x-a}{b} \right)^2 \, \right)\right)^{-1} \text{ .}$$
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  ``` cpp
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  namespace std {
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  template<class RealType = double>
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  class cauchy_distribution {
@@ -292,15 +282,11 @@ constructed.
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  ##### Class template `fisher_f_distribution` <a id="rand.dist.norm.f">[[rand.dist.norm.f]]</a>
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  A `fisher_f_distribution` random number distribution produces random
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  numbers x ≥ 0 distributed according to the probability density function
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- $$p(x\,|\,m,n) = \frac{\Gamma\big((m+n)/2\big)}{\Gamma(m/2) \; \Gamma(n/2)}
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- \cdot \left(\frac{m}{n}\right)^{m/2}
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- \cdot x^{(m/2)-1}
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- \cdot \left(1 + \frac{m x}{n}\right)^{-(m + n)/2}
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- \text{ .}$$
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  ``` cpp
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  namespace std {
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  template<class RealType = double>
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  class fisher_f_distribution {
@@ -367,15 +353,11 @@ RealType n() const;
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  constructed.
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  ##### Class template `student_t_distribution` <a id="rand.dist.norm.t">[[rand.dist.norm.t]]</a>
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  A `student_t_distribution` random number distribution produces random
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- numbers x distributed according to the probability density function
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- $$p(x\,|\,n) = \frac{1}{\sqrt{n \pi}}
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- \cdot \frac{\Gamma\big((n+1)/2\big)}{\Gamma(n/2)}
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- \cdot \left(1 + \frac{x^2}{n} \right)^{-(n+1)/2}
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- \text{ .}$$
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  ``` cpp
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  namespace std {
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  template<class RealType = double>
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  class student_t_distribution {
 
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  #### Normal distributions <a id="rand.dist.norm">[[rand.dist.norm]]</a>
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  ##### Class template `normal_distribution` <a id="rand.dist.norm.normal">[[rand.dist.norm.normal]]</a>
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  A `normal_distribution` random number distribution produces random
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+ numbers x distributed according to the probability density function in .
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+
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+ The distribution parameters μ and σ are also known as this
 
 
 
 
 
 
 
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  distribution’s *mean* and *standard deviation*.
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  ``` cpp
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  namespace std {
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  template<class RealType = double>
 
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  ##### Class template `lognormal_distribution` <a id="rand.dist.norm.lognormal">[[rand.dist.norm.lognormal]]</a>
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  A `lognormal_distribution` random number distribution produces random
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  numbers x > 0 distributed according to the probability density function
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+ in .
 
 
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  ``` cpp
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  namespace std {
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  template<class RealType = double>
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  class lognormal_distribution {
 
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  ##### Class template `chi_squared_distribution` <a id="rand.dist.norm.chisq">[[rand.dist.norm.chisq]]</a>
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  A `chi_squared_distribution` random number distribution produces random
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  numbers x > 0 distributed according to the probability density function
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+ in .
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  ``` cpp
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  namespace std {
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  template<class RealType = double>
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  class chi_squared_distribution {
 
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  constructed.
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  ##### Class template `cauchy_distribution` <a id="rand.dist.norm.cauchy">[[rand.dist.norm.cauchy]]</a>
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  A `cauchy_distribution` random number distribution produces random
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+ numbers x distributed according to the probability density function in .
 
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  ``` cpp
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  namespace std {
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  template<class RealType = double>
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  class cauchy_distribution {
 
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  ##### Class template `fisher_f_distribution` <a id="rand.dist.norm.f">[[rand.dist.norm.f]]</a>
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  A `fisher_f_distribution` random number distribution produces random
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  numbers x ≥ 0 distributed according to the probability density function
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+ in .
 
 
 
 
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  ``` cpp
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  namespace std {
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  template<class RealType = double>
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  class fisher_f_distribution {
 
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  constructed.
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  ##### Class template `student_t_distribution` <a id="rand.dist.norm.t">[[rand.dist.norm.t]]</a>
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  A `student_t_distribution` random number distribution produces random
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+ numbers x distributed according to the probability density function in .
 
 
 
 
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  ``` cpp
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  namespace std {
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  template<class RealType = double>
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  class student_t_distribution {