splint_R: A function to conduct the interpolation given data and fitted...

In be-green/quantspace: Quantile Regression via Quantile Spacing

A function to conduct the interpolation given data and fitted quantiles

Description

A function to conduct the interpolation given data and fitted quantiles

Usage

splint_R(
  y,
  quantiles,
  alphas,
  y2,
  tail_param_u,
  tail_param_l,
  q_shift,
  q_stretch,
  tails = "gaussian",
  distn = "c"
)

Arguments

y	a vector of quantile or pdf
quantiles	a matrix of size N b p
alphas	quantiles that were computed
y2	second derivatives
tail_param_u	the tail parameters for upper quantiles
tail_param_l	the tail parameters for lower quantiles
q_shift	normalization parameters
q_stretch	normalization parameters
tails	based on what distribution to compute the tails
distn	a string which indicates what type of distribution to return. See details.

Details

the distn argument takes on "p" to evaluate a PF, "c" to evaluate a CDF, and "q" to evaluate a quantile distribution.

Value

A vector of quantiles or density corresponding to y

be-green/quantspace documentation built on March 20, 2024, 5:30 p.m.