StudentT (FSharp.Stats) | FSharp.Stats

FSharp.Stats

StudentT Type

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

Student's T-distribution

Static members

Static member	Description
`StudentT.CDF(mu) (tau) (dof) (x)` Full Usage: `StudentT.CDF(mu) (tau) (dof) (x)` Parameters: mu : `float` - tau : `float` - dof : `float` - x : `float` - Returns: `float`	Computes the cumulative distribution function. mu : `float` tau : `float` dof : `float` x : `float` Returns: `float` Example
`StudentT.CheckParam(mu) (tau) (dof)` Full Usage: `StudentT.CheckParam(mu) (tau) (dof)` Parameters: mu : `'a` tau : `float` dof : `float`	mu : `'a` tau : `float` dof : `float`
`StudentT.Init(mu) (tau) (dof)` Full Usage: `StudentT.Init(mu) (tau) (dof)` Parameters: mu : `float` - tau : `float` - dof : `float` - Returns: `ContinuousDistribution<float, float>`	Initializes a Student's T-distribution mu : `float` tau : `float` dof : `float` Returns: `ContinuousDistribution<float, float>` Example
`StudentT.InvCDF(mu) (tau) (dof) (x)` Full Usage: `StudentT.InvCDF(mu) (tau) (dof) (x)` Parameters: mu : `'a` - tau : `float` - dof : `float` - x : `'b` - Returns: `'c`	Computes the inverse cumulative distribution function (quantile function). mu : `'a` tau : `float` dof : `float` x : `'b` Returns: `'c` Example
`StudentT.Mean(mu) (tau) (dof)` Full Usage: `StudentT.Mean(mu) (tau) (dof)` Parameters: mu : `'a` - tau : `float` - dof : `float` - Returns: `'a`	Computes the mean. mu : `'a` tau : `float` dof : `float` Returns: `'a` Example
`StudentT.Mode(mu) (tau) (dof)` Full Usage: `StudentT.Mode(mu) (tau) (dof)` Parameters: mu : `'a` - tau : `float` - dof : `float` - Returns: `'a`	Computes the mode. mu : `'a` tau : `float` dof : `float` Returns: `'a` Example
`StudentT.PDF(mu) (tau) (dof) (x)` Full Usage: `StudentT.PDF(mu) (tau) (dof) (x)` Parameters: mu : `float` - tau : `float` - dof : `float` - x : `float` - Returns: `float`	Computes the probability density function. mu : `float` tau : `float` dof : `float` x : `float` Returns: `float` Example
`StudentT.Sample(mu) (tau) (dof)` Full Usage: `StudentT.Sample(mu) (tau) (dof)` Parameters: mu : `float` - tau : `float` - dof : `float` - Returns: `float`	Produces a random sample using the current random number generator (from GetSampleGenerator()). mu : `float` tau : `float` dof : `float` Returns: `float` Example
`StudentT.StandardDeviation(mu) (tau) (dof)` Full Usage: `StudentT.StandardDeviation(mu) (tau) (dof)` Parameters: mu : `'a` - tau : `float` - dof : `float` - Returns: `float`	Computes the standard deviation. mu : `'a` tau : `float` dof : `float` Returns: `float` Example
`StudentT.Support(mu) (tau) (dof)` Full Usage: `StudentT.Support(mu) (tau) (dof)` Parameters: mu : `'a` - tau : `float` - dof : `float` - Returns: `Interval<float>`	Returns the support of the exponential distribution: (Negative Infinity, Positive Infinity). mu : `'a` tau : `float` dof : `float` Returns: `Interval<float>` Example
`StudentT.ToString(mu) (tau) (dof)` Full Usage: `StudentT.ToString(mu) (tau) (dof)` Parameters: mu : `float` - tau : `float` - dof : `float` - Returns: `string`	A string representation of the distribution. mu : `float` tau : `float` dof : `float` Returns: `string` Example
`StudentT.Variance(mu) (tau) (dof)` Full Usage: `StudentT.Variance(mu) (tau) (dof)` Parameters: mu : `'a` - tau : `float` - dof : `float` - Returns: `float`	Computes the variance. mu : `'a` tau : `float` dof : `float` Returns: `float` Example