hmmlt.gof.x: Goodness-of-fit in perpendicular dimension.
In DistanceDevelopment/hsltm: Line transect estimation with hidden state availability models
Description
Calculates goodness-of-fit in perpendicular dimension, plots fit, and returns p-value and
other stuff. Returns two p-values: p.ks is the Kolmogarov-Smirnov p-value (which is
based on only the largest difference between emprical and theoretical cdfs), and Cramer-von Mises
p-value (which is based on all cdf values).
Usage
1
hmmlt.gof.x(hmltm, ks.plot = TRUE)
Arguments
hmltm
fitted model, as output by est.hmltm
ks.plot
If TRUE, does Q-Q plot. Point corresponding to largest difference between
empirical and theoretical cdf (on which the Kolmogarov-Smirnov test is based) is circled in red.
DistanceDevelopment/hsltm documentation built on June 21, 2019, 2:22 p.m.
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Description
Calculates goodness-of-fit in perpendicular dimension, plots fit, and returns p-value and
other stuff. Returns two p-values: p.ks is the Kolmogarov-Smirnov p-value (which is
based on only the largest difference between emprical and theoretical cdfs), and Cramer-von Mises
p-value (which is based on all cdf values).
Usage
1 | hmmlt.gof.x(hmltm, ks.plot = TRUE)
|
Arguments
hmltm |
fitted model, as output by |
ks.plot |
If TRUE, does Q-Q plot. Point corresponding to largest difference between empirical and theoretical cdf (on which the Kolmogarov-Smirnov test is based) is circled in red. |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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