Exponential (FSharp.Stats)

Exponential Type

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

Exponential distribution.

Static members

Static member	Description
`Exponential.CDF(lambda) (x)` Full Usage: `Exponential.CDF(lambda) (x)` Parameters: lambda : `float` - x : `float` - Returns: `float`	Computes the cumulative distribution function. lambda : `float` x : `float` Returns: `float` Example
`Exponential.CheckParam(lambda)` Full Usage: `Exponential.CheckParam(lambda)` Parameters: lambda : `float`	lambda : `float`
`Exponential.Estimate(observations, ?weights)` Full Usage: `Exponential.Estimate(observations, ?weights)` Parameters: observations : `float[]` ?weights : `float[]` Returns: `ContinuousDistribution<float, float>`	Estimates a new Exponential distribution from a given set of observations. observations : `float[]` ?weights : `float[]` Returns: `ContinuousDistribution<float, float>`
`Exponential.Fit(observations, ?weights)` Full Usage: `Exponential.Fit(observations, ?weights)` Parameters: observations : `float[]` ?weights : `float[]` Returns: `float`	Fits the underlying distribution to a given set of observations. observations : `float[]` ?weights : `float[]` Returns: `float`
`Exponential.Init(lambda)` Full Usage: `Exponential.Init(lambda)` Parameters: lambda : `float` - Returns: `ContinuousDistribution<float, float>`	Initializes a Exponential distribution lambda : `float` Returns: `ContinuousDistribution<float, float>` Example
`Exponential.InvCDF(lambda) (x)` Full Usage: `Exponential.InvCDF(lambda) (x)` Parameters: lambda : `float` - x : `'a` - Returns: `'b`	Computes the inverse cumulative distribution function (quantile function). lambda : `float` x : `'a` Returns: `'b` Example
`Exponential.Mean(lambda)` Full Usage: `Exponential.Mean(lambda)` Parameters: lambda : `float` - Returns: `float`	Computes the mean. lambda : `float` Returns: `float` Example
`Exponential.Mode(lambda)` Full Usage: `Exponential.Mode(lambda)` Parameters: lambda : `float` - Returns: `float`	Computes the mean. lambda : `float` Returns: `float` Example
`Exponential.PDF(lambda) (x)` Full Usage: `Exponential.PDF(lambda) (x)` Parameters: lambda : `float` - x : `float` - Returns: `float`	Computes the probability density function. lambda : `float` x : `float` Returns: `float` Example
`Exponential.Sample(lambda)` Full Usage: `Exponential.Sample(lambda)` Parameters: lambda : `float` - Returns: `float`	Produces a random sample using the current random number generator (from GetSampleGenerator()). lambda : `float` Returns: `float` Example
`Exponential.StandardDeviation(lambda)` Full Usage: `Exponential.StandardDeviation(lambda)` Parameters: lambda : `float` - Returns: `float`	Computes the standard deviation. lambda : `float` Returns: `float` Example
`Exponential.Support()` Full Usage: `Exponential.Support()` Returns: `Interval<float>`	Returns: `Interval<float>`
`Exponential.ToString(lambda)` Full Usage: `Exponential.ToString(lambda)` Parameters: lambda : `float` - Returns: `string`	A string representation of the distribution. lambda : `float` Returns: `string` Example
`Exponential.Variance(lambda)` Full Usage: `Exponential.Variance(lambda)` Parameters: lambda : `float` - Returns: `float`	Computes the variance. lambda : `float` Returns: `float` Example