BoundedDensity {bde}

Class "BoundedDensity"

Description

This class deals with generic estimations of a bounded densities. The probability density function is approximated by providing a set of data points in a lower and upper bounded interval and their associated densities. Using this information, the methods implemented in the class can be used to compute densities, values of the distribution function, quantiles, sample the distribution and obtain graphical representations.

Objects from the Class

Objects can be created by using the generator function boundedDensity.

Slots

dataPointsCache:

a numeric vector containing points within the [lower.limit,upper.limit] interval

densityCache:

a numeric vector containing the density for each point in dataPointsCache

distributionCache:

a numeric vector used to cache the values of the distribution function. This slot is included to improve the performance of the methods when multiple calculations of the distribution function are used

lower.limit:

a numeric value for the lower limit of the bounded interval for the data

upper.limit:

a numeric value for the upper limit of the bounded interval for the data

Methods

density

See "density" for details

distribution

See "distribution" for details

quantile

See "quantile" for details

rsample

See "rsample" for details

plot

See "plot" for details

getdataPointsCache

See "getdataPointsCache" for details

getdensityCache

See "getdensityCache" for details

getdistributionCache

See "getdistributionCache" for details

Author(s)

Guzman Santafe, Borja Calvo and Aritz Perez

Examples

# data points and its densities
a <- seq(0,1,0.01)
b <- dbeta(a,5,10)

# create the density model
model <- boundedDensity(x=a,densities=b)

# examples of usual functions
density(model,0.5)

distribution(model,0.2,discreteApproximation=FALSE)
distribution(model,0.2,discreteApproximation=TRUE)
 
# graphical representation
hist(b,freq=FALSE)
lines(model, col="red",lwd=2)