as.paleoTS {paleoTS}

Make a Paleontological Time-series object

Description

Combines information into an object of class paleoTS

Usage

as.paleoTS(
  mm,
  vv,
  nn,
  tt,
  MM = NULL,
  genpars = NULL,
  label = NULL,
  start.age = NULL,
  oldest = c("first", "last"),
  reset.time = TRUE
)

Arguments

mm

vector of sample means

vv

vector of sample variances

nn

vector of sample sizes

tt

vector of sample ages

MM

vector of true means (simulated data)

genpars

generating parameters (simulated data)

label

optional, label for time-series

start.age

optional, age of oldest sample

oldest

value indicating if the oldest sample is first or last in the sequence

reset.time

logical; if TRUE, then change time scale to start at t=0 and adjust start.age accordingly

Details

This function combines data into a paleoTS object. For empirical data it may be more convenient to use read.paleoTS.

If sample ages decrease through the sequence, as if given in millions of years ago, tt will automatically be converted to time elapsed from the beginning of the sequence as long as reset.time = TRUE.

Value

a paleoTS object

Note

All model-fitting functions estimate the contribution of sampling noise to the observed differences between samples. They do this assuming that the trait is represented by sample means, which have sampling variances equal to variance divided by sample size, vv/nn. If one is interested in analyzing statistics other than the sample mean (medians, quantiles, or other statistics), use the the following procedure: set the statistic in question as the mm values, replace vv with a vector of the squared standard errors for each estimate (generated by other means, for example bootstrapping), and set all values of nn to one. When fitting such time-series, be sure to set the argument pool = FALSE.

See Also

read.paleoTS

Examples

x <- as.paleoTS(mm = rnorm(20), vv = rep(1, 20), nn = rep(25, 20), tt=0:19)
plot(x) # easier to use sim.Stasis()