Split ps and qs into those corresponding to discrete and continuous parts of a distribution.

Usage

split_disc_cont_ps_qs(
  ps,
  qs,
  dup_tol = 1e-06,
  zero_tol = 1e-12,
  is_hurdle = FALSE
)

ps: vector of probability levels
qs: vector of quantile values correponding to ps
dup_tol: numeric tolerance for identifying duplicated values indicating a discrete component of the distribution. If there is a run of values where each consecutive pair is closer together than the tolerance, all are labeled as duplicates even if not all values in the run are within the tolerance.
zero_tol: numeric tolerance for identifying values in qs that are (approximately) zero.
is_hurdle: boolean indicating whether or not this is a hurdle model. If so, qs of zero always indicate the presence of a point mass at 0. In this case, 0 is not included among the returned cont_qs. Setting this argument to TRUE is primarily appropriate when we are working with a distributional family that is bounded above 0 (and may have density 0 at 0) such as a lognormal.

named list with the following entries:

disc_weight: estimated numeric weight of the discrete part of the distribution.
disc_ps: estimated probabilities of discrete components. May be numeric(0) if there are no estimated discrete components.
disc_qs: locations of discrete components, corresponding to duplicated values in the input qs. May be numeric(0) if there are no discrete components.
cont_ps: probability levels for the continous part of the distribution
cont_qs: quantile values for the continous part of the distribution
disc_ps_range: a list of length equal to the number of point masses in the discrete distribution. Each entry is a numeric vector of length two with the value of the cdf approaching the point mass from the left and from the right.