Internal functions not designed to be used directly, but are all exported to make them visible to users.
kdenx(x, kerncentres, lambda, kernel = "gaussian")pkdenx(x, kerncentres, lambda, kernel = "gaussian")
bckdenxsimple(x, kerncentres, lambda, kernel = "gaussian")
pbckdenxsimple(x, kerncentres, lambda, kernel = "gaussian")
bckdenxcutnorm(x, kerncentres, lambda, kernel = "gaussian")
pbckdenxcutnorm(x, kerncentres, lambda, kernel = "gaussian")
bckdenxrenorm(x, kerncentres, lambda, kernel = "gaussian")
pbckdenxrenorm(x, kerncentres, lambda, kernel = "gaussian")
bckdenxreflect(x, kerncentres, lambda, kernel = "gaussian")
pbckdenxreflect(x, kerncentres, lambda, kernel = "gaussian")
pxb(x, lambda)
bckdenxbeta1(x, kerncentres, lambda, xmax)
pbckdenxbeta1(x, kerncentres, lambda, xmax)
bckdenxbeta2(x, kerncentres, lambda, xmax)
pbckdenxbeta2(x, kerncentres, lambda, xmax)
bckdenxgamma1(x, kerncentres, lambda)
pbckdenxgamma1(x, kerncentres, lambda)
bckdenxgamma2(x, kerncentres, lambda)
pbckdenxgamma2(x, kerncentres, lambda)
bckdenxcopula(x, kerncentres, lambda, xmax)
pbckdenxcopula(x, kerncentres, lambda, xmax)
pbckdenxlog(x, kerncentres, lambda, offset, kernel = "gaussian")
pbckdenxnn(x, kerncentres, lambda, kernel = "gaussian", nn)
qmix(x, u, epsilon)
qmixprime(x, u, epsilon)
qgbgmix(x, ul, ur, epsilon)
qgbgmixprime(x, ul, ur, epsilon)
pscounts(x, beta, design.knots, degree)
quantiles
kernel centres (typically sample data vector or scalar)
bandwidth for kernel (as half-width of kernel) or NULL
kernel name (default = "gaussian"
)
upper bound on support (copula and beta kernels only) or NULL
offset added to kernel centres (logtrans only) or NULL
non-negativity correction method (simple boundary correction only)
threshold
interval half-width
lower tail threshold
upper tail threshold
vector of B-spline coefficients (required)
spline knots for splineDesign function
degree of B-splines (0 is constant, 1 is linear, etc.)
Based on code by Anna MacDonald produced for MATLAB.
Internal functions not designed to be used directly. No error checking of the inputs is carried out, so user must be know what they are doing. They are undocumented, but are made visible to the user.
Mostly, these are used in the kernel density estimation functions.