diveMove (version 0.8.3)

bout-methods: Methods for Plotting and Extracting the Bout Ending Criterion

Description

Plot results from fitted mixture of 2-process Poisson models, and calculate the bout ending criterion.

Usage

## S3 method for class 'nls':
plotBouts(fit, \ldots)
## S3 method for class 'mle':
plotBouts(fit, x, \ldots)
## S3 method for class 'nls':
bec2(fit)
## S3 method for class 'mle':
bec2(fit)

Arguments

fit

nls or mle object.

x

Numeric object with variable modelled.

...

Arguments passed to the underlying plotBouts2.nls and plotBouts2.mle.

References

Langton, S.; Collett, D. and Sibly, R. (1995) Splitting behaviour into bouts; a maximum likelihood approach. Behaviour 132, 9-10.

Luque, S. P. and Guinet, C. (2007) A maximum likelihood approach for identifying dive bouts improves accuracy, precision, and objectivity. Behaviour, in press.

Mori, Y.; Yoda, K. and Sato, K. (2001) Defining dive bouts using a sequential differences analysis. Behaviour 138, 1451-1466.

Sibly, R.; Nott, H. and Fletcher, D. (1990) Splitting behaviour into bouts. Animal Behaviour 39, 63-69.

See Also

bouts.mle, bouts2.nls for examples.