Uniform (FSharp.Stats)

Uniform Type

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

Uniform distribution.

Static members

Static member	Description
`Uniform.CDF(min) (max) (x)` Full Usage: `Uniform.CDF(min) (max) (x)` Parameters: min : `float` - max : `float` - x : `float` - Returns: `float`	Computes the cumulative distribution function. min : `float` max : `float` x : `float` Returns: `float` Example
`Uniform.CheckParam(min) (max)` Full Usage: `Uniform.CheckParam(min) (max)` Parameters: min : `float` max : `float`	min : `float` max : `float`
`Uniform.Estimate(observations)` Full Usage: `Uniform.Estimate(observations)` Parameters: observations : `float[]` Returns: `ContinuousDistribution<float, float>`	Estimates a new Uniform distribution from a given set of observations. observations : `float[]` Returns: `ContinuousDistribution<float, float>`
`Uniform.Fit(observations)` Full Usage: `Uniform.Fit(observations)` Parameters: observations : `float[]` Returns: `float * float`	Fits the underlying distribution to a given set of observations. observations : `float[]` Returns: `float * float`
`Uniform.Init(min) (max)` Full Usage: `Uniform.Init(min) (max)` Parameters: min : `float` - max : `float` - Returns: `ContinuousDistribution<float, float>`	Initializes a uniform distribution min : `float` max : `float` Returns: `ContinuousDistribution<float, float>` Example
`Uniform.InvCDF(min) (max) (x)` Full Usage: `Uniform.InvCDF(min) (max) (x)` Parameters: min : `float` - max : `float` - x : `'a` - Returns: `'b`	Computes the inverse cumulative distribution function (quantile function). min : `float` max : `float` x : `'a` Returns: `'b` Example
`Uniform.Mean(min) (max)` Full Usage: `Uniform.Mean(min) (max)` Parameters: min : `float` - max : `float` - Returns: `float`	Computes the mean. min : `float` max : `float` Returns: `float` Example
`Uniform.Mode(min) (max)` Full Usage: `Uniform.Mode(min) (max)` Parameters: min : `float` - max : `float` - Returns: `float`	Computes the mode. min : `float` max : `float` Returns: `float` Example
`Uniform.PDF(min) (max) (x)` Full Usage: `Uniform.PDF(min) (max) (x)` Parameters: min : `float` - max : `float` - x : `float` - Returns: `float`	Computes the probability density function. min : `float` max : `float` x : `float` Returns: `float` Example
`Uniform.Sample(min) (max)` Full Usage: `Uniform.Sample(min) (max)` Parameters: min : `float` - max : `float` - Returns: `float`	Produces a random sample using the current random number generator (from GetSampleGenerator()). min : `float` max : `float` Returns: `float` Example
`Uniform.StandardDeviation(min) (max)` Full Usage: `Uniform.StandardDeviation(min) (max)` Parameters: min : `float` - max : `float` - Returns: `float`	Computes the standard deviation. min : `float` max : `float` Returns: `float` Example
`Uniform.Support(min) (max)` Full Usage: `Uniform.Support(min) (max)` Parameters: min : `float` - max : `float` - Returns: `Interval<float>`	Returns the support of the exponential distribution: [0, Positive Infinity). min : `float` max : `float` Returns: `Interval<float>` Example
`Uniform.ToString(min) (max)` Full Usage: `Uniform.ToString(min) (max)` Parameters: min : `float` - max : `float` - Returns: `string`	A string representation of the distribution. min : `float` max : `float` Returns: `string` Example
`Uniform.Variance(min) (max)` Full Usage: `Uniform.Variance(min) (max)` Parameters: min : `float` - max : `float` - Returns: `float`	Computes the variance. min : `float` max : `float` Returns: `float` Example