optBrokenstick: Fitting automatic brokenstick models
In SESman/rbl: Biologging tools for diving predators in R

Description Usage Arguments Value See Also Examples

optBrokenstick is similar to brokenstick except that a cost function can be used to determine the optimal number of points.

1 2	optBrokenstick(x, y = NULL, threshold, cost = max_dist_cost, npmin = 2, npmax = Inf, start = NULL, na.action, ...)

`x`	The x data. Note that the `x` values have to be sorted. Can also be a list of `x` and `y` data as returned by `xy.coords`.
`y`	The y data.
`threshold`	A threshold value for the cost function to be used instead of the minimum. If provided the search of a local minimum in the cost function is abandoned.
`cost`	The cost function to use. Some are included in the package such as `max_dist_cost`, `dist_per_pt_cost`, `rss_cost`, `dzi_cost` etc. Feel free to use a custom one.
`npmin`	Minimun number of points.
`npmax`	Maximum number of points.
`start`	Some starting points to start the algorithm with.
`na.action`	A function which indicates what should happen when the data contain `NAs`. The default is set by the `na.action` setting of `options`, and is `na.fail` if that is unset. The "factory-fresh" default is `na.omit`. Another possible value is `NULL`, no action. Value `na.exclude` can be useful.
`...`	Further arguments to be passed to `bsmfit` such as `eco.mem`.

Same as brokenstick with the value of the cost function.

brokenstick and predict.bsm, residuals.bsm, update.bsm, summary.bsm, coef.bsm, plot.bsm, as.data.frame.bsm for other functions with a S3 method for bsm objects.

data(exses)
dv <- tdrply(identity, 1:2, no = 90, obj = exses)[[1]]

bsm_6p <- brokenstick(dv, npts = 6)
plot(bsm_6p, data = TRUE)

bsm_30m <- optBrokenstick(dv, threshold = 30, cost = max_dist_cost) 
plot(bsm_30m, add = TRUE, col = 2, lty = 2, enumerate = TRUE, 
     col.pts = (bsm_30m$pts.no > 5) + 1)

bsm_5m <- optBrokenstick(dv, threshold = 5, cost = max_dist_cost) 
plot(bsm_5m, add = TRUE, col = 3, lty = 3, enumerate = TRUE, 
     col.pts = (bsm_5m$pts.no > max(bsm_30m$pts.no)) + (bsm_5m$pts.no > 5) + 1)