intRvals
Package intRvals calculates means and variances of arrival intervals (and arrival rates) corrected for missed arrival observations, and compares means and variances of groups of interval data.
Installation in R
library(devtools)
install_github("adokter/intRvals")
General
The central function of package intRvals
is estinterval
, which is used to estimate the mean arrival interval (and its standard deviation) from interval data with missed arrivals. This is achieved by fitting the theoretical probability density intervalpdf
to the interval data
The package can be used to analyse general interval data where intervals are derived from distinct arrival observations. For example, the authors have used it to analyze dropping intervals of grazing geese for estimating their faecal output.
Intervals are defined as the time between observed arrival events (e.g. the time between one excreted droppings to the next) The package provides a way of taking into account missed observations (e.g. defecations), which lead to occasional observed intervals at integer multiples of the true arrival interval.
Typical workflow
- Fit interval model
m
to an interval datasetd
usingestinterval
, as inm=estinterval(d)
. - Visually inspect model fits using
plot.intRvals
, as inplot(m)
. - Use
anova.intRvals
to check whether the missed event probability was signficantly different from zero, as inanova(m)
- Also use
anova.intRvals
to perform model selection between competing modelsm1
,m2
for the same interval datasetd
, as inanova(m1,m2)
- Compare means and variances between different interval datasets
d1
,d2
usingttest
andvartest
Other useful functionality
fold
provides functionality to fold observed intervals back to their fundamental intervalfundamental
tests which intervals are fundamental, i.e. intervals not containing a missed arrival observationinterval2rate
converts interval estimates to ratespartition
estimates and tests for the presence of within-subject variationintervalsim
simulates a set of observed intervals
The package comes with a example interval dataset goosedrop
References
- Dokter, A.M., et al. 2017. Analysing time-ordered event data with missed observations, Ecology and Evolution, 2017, in press.
- Bédard, J. & Gauthier, G. 1986. Assessment of faecal output in geese. Journal of Applied Ecology, 23, 77-90.
- Owen, M. 1971. The Selection of Feeding Site by White-Fronted Geese in Winter. Journal of Applied Ecology 8: 905-917.