auto.corr.test.decel: Applying the autocorrelation test to the decelerated...

In klvoje/adePEM: Evaluate the adequacy of within-lineage phenotypic evolution models

Applying the autocorrelation test to the decelerated evolution model

Description

Investigates if the decelerated evolution model is an adequate statistical description of an evolutionary time series by applying the autocorrelation test.

Usage

auto.corr.test.decel(y, r = NULL, vstep = NULL, nrep = 1000,
  conf = 0.95, plot = TRUE, save.replicates = TRUE)

Arguments

y	a paleoTS object
r	parameter describing the decrease in rate of evolution through time. r is restricted to values smaller than zero (the model reduces to the BM model when r = 0).
vstep	the variance of the step distribution estimated from the observed data.
nrep	number of iterations in the parametric bootstrap (number of simulated time series); default is 1000.
conf	confidence level for judging whether a model is an adequate statistical description of the data. Number must be between 0 and 1. A higher number means less strict judgment of whether a model is adequate; default is 0.95. Tests are two-tailed (except for the net evolution test), which means a model is judged adequate if the observed test statistic is within the 2.5 percent of the extreme values of the calculated test statistics on the simulated data given the default confidence value of 0.95.
plot	logical; if TRUE, the value of the test statistic calculated based on the observed fossil time series is plotted on the distribution of test statistics calculated on the simulated time series; default is TRUE.
save.replicates	logical; if TRUE, the values of the test statistic calculated on the simulated time series is saved and can be accessed later for plotting purposes; default is TRUE.

Details

This function calculates the autocorrelation in a vector of sample means defined as the correlation of the first n-1 observations with the last n-1. The autocorrelation is calculated directly on the sample means if the evaluated model is stasis. If a different model is evaluated (e.g. random walk or directional trend), the data is detrended prior to the calculation of autocorrelation.

Value

First part of the output summarizes the number of iterations in the parametric boostrap and the confidence level for judging whether a model is an adequate statistical description of the data. The last part of the output is:

estimate	The calculated test statistic on the observed data.
min.sim	The smallest test statistic calculated on the simulated data.
max.sim	The largest test statistic calculated on the simulated data.
p-value	Not a real p-value, but is calculated as the fraction of simulated test statistics that is larger (or smaller) than the calculated test statistic on the observed data divided by 0.5. A value of 1 means 50 percent of the test statistics on the simulated data are larger and smaller than the calculated statistic on the observed data. A value of 0.10 means 90 percent of the test statistics on the simulated data are larger or smaller than the test statistic on the observed time series.
result	Whether the model PASSED or FAILED the adequacy test. The outcome depends on the confidence level.

Author(s)

Kjetil L. Voje

References

Voje, K.L. 2018. Assessing adequacy of models of phyletic evolution in the fossil record. Methods in Ecology and Evoluton. (in press).

Voje, K.L., Starrfelt, J., and Liow, L.H. 2018. Model adequacy and microevolutionary explanations for stasis in the fossil record. The American Naturalist. 191:509-523.

See Also

fit3adequasy.EB, auto.corr.test.trend, auto.corr.test.stasis

Examples

## generate a paleoTS objects by simulating early burst
x <- sim.accel_decel(ns=40, r=-1, vs=0.1)

## investigate if the time series pass the adequasy test
auto.corr.test.decel(x)

klvoje/adePEM documentation built on Feb. 24, 2023, 1:28 p.m.