corEns: Ensemble correlation

In nickmckay/GeoChronR: Tools to Analyze and Visualize Time-Uncertain Data

Ensemble correlation

Description

Primary function for calculating correlation ensembles

Usage

corEns(
  time.1,
  values.1,
  time.2,
  values.2,
  bin.vec = NA,
  bin.step = NA,
  bin.fun = mean,
  max.ens = NA,
  percentiles = c(0.025, 0.25, 0.5, 0.75, 0.975),
  min.obs = 10,
  fdr.qlevel = 0.05,
  gaussianize = TRUE,
  ...
)

Arguments

time.1	matrix of age/time ensembles, or single column
values.1	matrix of values ensembles, or single column
time.2	matrix of age/time ensembles, or single column
values.2	matrix of values ensembles, or single column
bin.vec	vector of bin edges for binning step
bin.step	spacing of bins, used to build bin step
bin.fun	function to use during binning (mean, sd, and sum all work)
max.ens	Maximum number of ensembles to use
percentiles	quantiles to calculate for regression parameters
min.obs	minimum number of points required to calculate regression
fdr.qlevel	target false discovery rate (most users won't want to change this)
gaussianize	Convert data to Gaussian distribution before correlating?
...	Arguments passed on to corMatrix ens.1 matrix of age-uncertain columns to correlate and calculate p-values ens.2 matrix of age-uncertain columns to correlate and calculate p-values isospectral estimate significance using the Ebisuzaki method (default = TRUE) isopersistent estimate significance using the isopersistence method (default = FALSE) p.ens number of ensemble members to use for isospectral and/or isopersistent methods (default = 100) cor.method correlation method to pass to cor() "pearson" (default), "kendall", or "spearman". Note that because the standard Student's T-test for significance is inappropriate for Kendall's Tau correlations, the raw and effective-N significance estimates will be NA when using "kendall"

Value

list of ensemble output and percentile information

Long-form example

View a full-fledged example of how to use this function.

Author(s)

Nick McKay

nickmckay/GeoChronR documentation built on April 9, 2024, 5:26 a.m.