Binomial (FSharp.Stats)

Binomial Type

Namespace: FSharp.Stats.Distributions.Discrete
Assembly: FSharp.Stats.dll
Base Type: obj

Binomial distribution

Static members

Static member	Description
`Binomial.CDF(p) (n) (x)` Full Usage: `Binomial.CDF(p) (n) (x)` Parameters: p : `float` n : `int` x : `float` Returns: `float`	Computes the cumulative distribution function at x, i.e. P(X <= x). p : `float` n : `int` x : `float` Returns: `float`
`Binomial.CheckParam(p) (n)` Full Usage: `Binomial.CheckParam(p) (n)` Parameters: p : `float` n : `int`	p : `float` n : `int`
`Binomial.Estimate(n) (observations)` Full Usage: `Binomial.Estimate(n) (observations)` Parameters: n : `int` observations : `float[]` Returns: `DiscreteDistribution<float, int>`	Estimates a new Binomial distribution from a given set of observations. n : `int` observations : `float[]` Returns: `DiscreteDistribution<float, int>`
`Binomial.Fit(n) (observations)` Full Usage: `Binomial.Fit(n) (observations)` Parameters: n : `int` observations : `float[]` Returns: `float`	Fits the underlying distribution to a given set of observations. n : `int` observations : `float[]` Returns: `float`
`Binomial.Init(p) (n)` Full Usage: `Binomial.Init(p) (n)` Parameters: p : `float` - n : `int` - Returns: `DiscreteDistribution<float, int>`	Initializes a Binomial distribution p : `float` n : `int` Returns: `DiscreteDistribution<float, int>` Example
`Binomial.InvCDF(p) (n) (x)` Full Usage: `Binomial.InvCDF(p) (n) (x)` Parameters: p : `float` n : `int` x : `float` Returns: `'a`	Computes the inverse cumulative distribution function (quantile function). p : `float` n : `int` x : `float` Returns: `'a`
`Binomial.Mean(p) (n)` Full Usage: `Binomial.Mean(p) (n)` Parameters: p : `float` - n : `int` - Returns: `float`	Computes the mean. p : `float` n : `int` Returns: `float` Example
`Binomial.Mode(p) (n)` Full Usage: `Binomial.Mode(p) (n)` Parameters: p : `float` - n : `int` - Returns: `int`	Computes the mode. p : `float` n : `int` Returns: `int` Example
`Binomial.PMF(p) (n) (k)` Full Usage: `Binomial.PMF(p) (n) (k)` Parameters: p : `float` - n : `int` - k : `int` - Returns: `float`	Computes the probability mass function at k, i.e. P(K = k) p : `float` n : `int` k : `int` Returns: `float` Example
`Binomial.Sample(p) (n)` Full Usage: `Binomial.Sample(p) (n)` Parameters: p : `float` - n : `int` - Returns: `int`	Produces a random sample using the current random number generator (from GetSampleGenerator()). p : `float` n : `int` Returns: `int` Example
`Binomial.StandardDeviation(p) (n)` Full Usage: `Binomial.StandardDeviation(p) (n)` Parameters: p : `float` - n : `int` - Returns: `float`	Computes the standard deviation. p : `float` n : `int` Returns: `float` Example
`Binomial.Support(p) (n)` Full Usage: `Binomial.Support(p) (n)` Parameters: p : `float` - n : `int` - Returns: `Interval<int>`	Returns the support of the Binomial distribution: (0., n). p : `float` n : `int` Returns: `Interval<int>` Example
`Binomial.ToString(p) (n)` Full Usage: `Binomial.ToString(p) (n)` Parameters: p : `float` - n : `int` - Returns: `string`	A string representation of the distribution. p : `float` n : `int` Returns: `string` Example
`Binomial.Variance(p) (n)` Full Usage: `Binomial.Variance(p) (n)` Parameters: p : `float` - n : `int` - Returns: `float`	Computes the variance. p : `float` n : `int` Returns: `float` Example