estimate_ci: Calculate confidence intervals using bootstrap of any...

In phenesse: Estimate Phenological Metrics using Presence-Only Data

Description

Calculate confidence intervals using bootstrap of any statistical function of interest.

Usage

estimate_ci(
  observations,
  .f,
  n_boots,
  parallelize = "no",
  ncpus = getOption("boot.ncpus", 1L),
  cl = NULL,
  type = "perc",
  conf = 0.95
)

Arguments

observations	is a vector of dates/time of observations given as numeric values
.f	function to use
n_boots	is the number of bootstraps you want to run to create the CIs
parallelize	The type of parallel operation to be used (if any). If missing, the default is that no parallelization will occur. Parallelization options are "multicore" and "snow"
ncpus	An integer that represents the number of processes to be used in parallel operation.
cl	An optional parallel or snow cluster for use if parallel = "snow". If not supplied, a cluster on the local machine is created for the duration of the boot call.
type	A vector of character strings representing the type of intervals required to calculate the CI. Defaults to "perc". See ??boot.ci for more information.
conf	The confidence level wanted. Defaults to 95% CI.

Value

A data frame with estimate, and the lower and upper points of its confidence interval

phenesse documentation built on July 29, 2020, 1:06 a.m.