Interpolate quantiles and return a cumulative distribution function

interpolate_quantiles(object, ...)

# S3 method for qs
interpolate_quantiles(
  object,
  newdata = NULL,
  grid = seq_quant(0, 1, by = 0.01),
  parallel = T,
  ncores = getCores(),
  row_thresh = 20,
  tails = "gaussian",
  distn = "q",
  ...
)

# S3 method for matrix
interpolate_quantiles(
  object,
  alphas,
  grid = seq_quant(0, 1, by = 0.01),
  parallel = T,
  ncores = getCores(),
  row_thresh = 100,
  tails = "gaussian",
  distn = "q",
  ...
)

Arguments

object

either matrix of quantiles or a fitted model with a relevant method to dispatch

...

other arguments passed to interpolate quantiles

newdata

New data to use when calculating quantiles to interpolate

grid

grid along which to evaluate the CDF

parallel

whether to work in parallel

ncores

number of cores to use

row_thresh

required minimum number of observations to use parallel processing

tails

what distribution to use when fitting the tails, either "gaussian" or "exponential"

distn

what to return, q for quantile, c for cdf, p for pdf

alphas

values those quantiles are fit to