mrv_histogram {ROOPSD}

mrv_histogram

Description

Multivariate rv_histogram distribution in OOP way.

Details

Used for a multivariate dataset, fit each marge

Public fields

n_features

[integer] Number of features (dimensions)

law_

[list] List of marginal distributions

Methods

Public methods

• mrv_histogram$new()

• mrv_histogram$fit()

• mrv_histogram$rvs()

• mrv_histogram$cdf()

• mrv_histogram$sf()

• mrv_histogram$icdf()

• mrv_histogram$isf()

• mrv_histogram$clone()

Method new()

Create a new mrv_histogram object.

Usage

mrv_histogram$new(...)

Arguments

...

If a param 'Y' is given, the fit method is called with '...'.

Returns

A new 'mrv_histogram' object.

Method fit()

Fit method for the histograms

Usage

mrv_histogram$fit(Y, bins = as.integer(100))

Arguments

Y

[vector] Dataset to infer the histogram

bins

[list or vector or integer] bins values

Returns

'self'

Method rvs()

Generation sample from the histogram

Usage

mrv_histogram$rvs(n = 1)

Arguments

n

[integer] Number of samples drawn

Returns

A matrix of samples

Method cdf()

Cumulative Distribution Function

Usage

mrv_histogram$cdf(q)

Arguments

q

[vector] Quantiles to compute the CDF

Returns

cdf values

Method sf()

Survival Function

Usage

mrv_histogram$sf(q)

Arguments

q

[vector] Quantiles to compute the SF

Returns

sf values

Method icdf()

Inverse of Cumulative Distribution Function

Usage

mrv_histogram$icdf(p)

Arguments

p

[vector] Probabilities to compute the CDF

Returns

icdf values

Method isf()

Inverse of Survival Function

Usage

mrv_histogram$isf(p)

Arguments

p

[vector] Probabilities to compute the SF

Returns

isf values

Method clone()

The objects of this class are cloneable with this method.

Usage

mrv_histogram$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

## Generate sample
X = matrix( stats::rnorm( n = 10000 ) , ncol = 4 )

## And fit it
rvX = mrv_histogram$new()
rvX$fit(X)