fit3adequacy.OU: Applying 3 adequacy tests to the Random walk model

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

Applying 3 adequacy tests to the Random walk model

Description

Investigating if the Random walk model is an adequate statistical description of an evolutionary time series by applying the following tests (1) autocorrelation (2) runs test, and (3) constant variation.

Usage

fit3adequacy.OU(y, nrep = 1000, conf = 0.95, plot = TRUE)

Arguments

y	a paleoTS object
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, 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.
vstep	the variance of the step distribution. This parameter is automatically estimated from the data, if not set by the user (usually not recommended).

Details

A wrapper function for investigating adequacy of the directional trend model applying all three tests at the same time.

Value

First part of the output summarizes the number of iterations in the parametric bootstrap and the confidence level for judging whether a model is an adequate statistical description of the data. The last part of the output is a data frame with the adequacy tests as columns and the following rows:

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

fit3adequacy.trend, fit4adequacy.stasis

Examples

## generate a paleoTS objects by simulating random walk
x <- sim.GRW(ns=40, ms=0, vs=0.1)

## Investigate if the random walk model is an adequate description of the data
fit3adequacy.RW(x)

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