mrv_histogram {ROOPSD} | R Documentation |
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
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)