Abstract class that cannot be constructed directly.
Returns error. Abstract classes cannot be constructed directly.
distr6::Distribution -> Kernel
packageDeprecated, use $packages instead.
packagesPackages required to be installed in order to construct the distribution.
new()Creates a new instance of this R6 class.
Kernel$new(decorators = NULL, support = Interval$new(-1, 1))
decorators(character())
Decorators to add to the distribution during construction.
support[set6::Set]
Support of the distribution.
mode()Calculates the mode of the distribution.
Kernel$mode(which = "all")
which(character(1) | numeric(1)
Ignored if distribution is unimodal. Otherwise "all" returns all modes, otherwise specifies
which mode to return.
mean()Calculates the mean (expectation) of the distribution.
Kernel$mean(...)
...Unused.
median()Calculates the median of the distribution.
Kernel$median()
pdfSquared2Norm()The squared 2-norm of the pdf is defined by $$\int_a^b (f_X(u))^2 du$$ where X is the Distribution, \(f_X\) is its pdf and \(a, b\) are the distribution support limits.
Kernel$pdfSquared2Norm(x = 0, upper = Inf)
x(numeric(1))
Amount to shift the result.
upper(numeric(1))
Upper limit of the integral.
cdfSquared2Norm()The squared 2-norm of the cdf is defined by $$\int_a^b (F_X(u))^2 du$$ where X is the Distribution, \(F_X\) is its pdf and \(a, b\) are the distribution support limits.
Kernel$cdfSquared2Norm(x = 0, upper = Inf)
x(numeric(1))
Amount to shift the result.
upper(numeric(1))
Upper limit of the integral.
skewness()The skewness of a distribution is defined by the third standardised moment, $$sk_X = E_X[\frac{x - \mu}{\sigma}^3]$$ where \(E_X\) is the expectation of distribution X, \(\mu\) is the mean of the distribution and \(\sigma\) is the standard deviation of the distribution.
Kernel$skewness(...)
...Unused.
clone()The objects of this class are cloneable with this method.
Kernel$clone(deep = FALSE)
deepWhether to make a deep clone.