paleoTS (version 0.5-1)

test.var.het: Variance heterogeneity test

Description

Tests for heterogeneity of sample variances in a paleoTS object.

Usage

test.var.het(y, method = "Bartlett")
pool.var(y, nn = NULL, minN = NULL, ret.paleoTS=FALSE)

Arguments

y

a paleoTS object

method

test to be used; currently only Bartlett's test is implemented

nn

if y is a vector of variances, nn is a vector of sample sizes

minN

minimum sample size; samples with n < minN have their variances replaced by the pooled variance across all samples.

ret.paleoTS

logical, indicating if the function should return a new paleoTS object with variances replaced by pooled variance.

Value

Function pool.var either returns a paeloTS object, or the pooled variance. Function test.var.het returns a list with the following elements relevant to Bartlett's test

stat

test statistic for Bartlett's test

p.value

P-vlaue for statistical test

df

degrees of freedom, equal to one fewer than the number of samples

Details

Tests for variance heterogeneity among samples. In the absence of evidence for heterogeniety, it may be desirable to replace individual estimates of phenotypic variance with a variance estimate pooled over all samples. Function pool.var is used internally in test.var.het. It returns the value of the pooled variance.

References

Hunt, G. 2006. Fitting and comparing models of phyletic evolution: random walks and beyond. Paleobiology 32:578--601.

Sokal, R. and F. J. Rohlf 1995. Biometry, 3rd Ed.

Examples

# NOT RUN {
# look at stickleback data
data(dorsal.spines)
ds<- sub.paleoTS(dorsal.spines, ok=dorsal.spines$nn>=1)	# drop missing data
ds2<- pool.var(ds, minN=5, ret.paleoTS=TRUE)
plot(ds2)
# }