Description Usage Arguments Details Author(s) Examples

View source: R/vis.concurvity.R

Plot measures of how much one term in the model could be explained by another. When values are high, one should consider re-running variable selection with one of the offending variables removed to check for stability in term selection.

1 | ```
vis.concurvity(model, type = "estimate")
``` |

`model` |
fitted model |

`type` |
concurvity measure to plot, see |

These methods are considered somewhat experimental at this time. Consult `concurvity`

for more information on how concurvity measures are calculated.

David L Miller

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | ```
## Not run:
library(Distance)
library(dsm)
# load the Gulf of Mexico dolphin data (see ?mexdolphins)
data(mexdolphins)
# fit a detection function and look at the summary
hr.model <- ds(distdata, max(distdata$distance),
key = "hr", adjustment = NULL)
# fit a simple smooth of x and y to counts
mod1 <- dsm(count~s(x,y)+s(depth), hr.model, segdata, obsdata)
# visualise concurvity using the "estimate" metric
vis.concurvity(mod1)
## End(Not run)
``` |

dsm documentation built on July 1, 2018, 9:06 a.m.

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