| rv_histogram {ROOPSD} | R Documentation |
rv_histogram
Description
rv_histogram distribution in OOP way.
Details
Use quantile to fit the histogram
Public fields
min[double] min value for the estimation
max[double] max value for the estimation
tol[double] numerical tolerance
Methods
Public methods
Method new()
Create a new rv_histogram object.
Usage
rv_histogram$new(...)
Arguments
...If a param 'Y' is given, the fit method is called with '...'.
Returns
A new 'rv_histogram' object.
Method rvs()
Generation sample from the histogram
Usage
rv_histogram$rvs(n)
Arguments
n[integer] Number of samples drawn
Returns
A vector of samples
Method density()
Density function
Usage
rv_histogram$density(x)
Arguments
x[vector] Values to compute the density
Returns
density
Method logdensity()
Log density function
Usage
rv_histogram$logdensity(x)
Arguments
x[vector] Values to compute the log-density
Returns
the log density
Method cdf()
Cumulative Distribution Function
Usage
rv_histogram$cdf(q)
Arguments
q[vector] Quantiles to compute the CDF
Returns
cdf values
Method icdf()
Inverse of Cumulative Distribution Function
Usage
rv_histogram$icdf(p)
Arguments
p[vector] Probabilities to compute the CDF
Returns
icdf values
Method sf()
Survival Function
Usage
rv_histogram$sf(q)
Arguments
q[vector] Quantiles to compute the SF
Returns
sf values
Method isf()
Inverse of Survival Function
Usage
rv_histogram$isf(p)
Arguments
p[vector] Probabilities to compute the SF
Returns
isf values
Method fit()
Fit method for the histograms
Usage
rv_histogram$fit(Y, bins = as.integer(1000))
Arguments
Y[vector] Dataset to infer the histogram
bins[vector or integer] bins values
Returns
'self'
Method clone()
The objects of this class are cloneable with this method.
Usage
rv_histogram$clone(deep = FALSE)
Arguments
deepWhether to make a deep clone.
Examples
## Generate sample
X = numeric(10000)
X[1:5000] = stats::rnorm( n = 5000 , mean = 2 , sd = 1 )
X[5000:10000] = stats::rexp( n = 5000 , rate = 1 )
## And fit it
rvX = rv_histogram$new()
rvX$fit(X)