corrMove: Calculate the movement correlation indices
In jmcalabrese/corrMove: Analyze Correlated Movements in Multi-Individual Datasets

Description Usage Arguments Details Value Author(s)

Selects the AICc best model for each partition and returns the corresponding point estimate and 95% confidence intervals for each MCI conditional on the selected model.

1	corrMove(data, prts)

`data`	A corrData object generated by as.corrData.
`prts`	A vector of partition points, generated by findPrts.

One estimate for each index, plus confidence intervals on each estimate, is produced for each partition in the data. These single values of each partition are repeated for each timestamp within a given partition for plotting purposes. Returns a value of 0 for both the point estimate and confidence interval for any MCI that cannot be produced by the selected model. For example, if the CU (correlated drift, uncorrelated diffusion) model is selected for a given partition, the diffusive correlation index point estimate and confidence interval limits will all be returned as 0, as there is no diffusive correlation in the CU model.

A dataframe consisting of the estimated values of each of the three MCIs and their corresponding confidence intervals, the selected model, and the partition number, for each timestamp in the dataset.

Justin M. Calabrese

jmcalabrese/corrMove documentation built on May 29, 2019, 1:04 a.m.