Description Usage Arguments Details Author(s) References See Also Examples
This function is analogous to the diagnose.ppm
function of the spatstat
package.
1 2 |
object |
A fitted regularisation path of point process models. The diagnostic plots will be created for the model that optimises the given criterion. |
... |
Other arguments for producing diagnostic plots, as given by the |
See the help file for diagnose.ppm
in the spatstat
package for further details of diagnostic plots.
Ian W. Renner
Baddeley, A.J. & Turner, R. (2005). Spatstat: an R package for analyzing spatial point patterns. Journal of Statistical Software 12, 1-42.
envelope.ppmlasso
, for other goodness-of-fit functions inherited from spatstat
.
1 2 3 4 5 6 | data(BlueMountains)
sub.env = BlueMountains$env[BlueMountains$env$Y > 6270 & BlueMountains$env$X > 300,]
sub.euc = BlueMountains$eucalypt[BlueMountains$eucalypt$Y > 6270 & BlueMountains$eucalypt$X > 300,]
ppm.form = ~ poly(FC, TMP_MIN, TMP_MAX, RAIN_ANN, degree=2) + poly(D_MAIN_RDS, D_URBAN, degree=2)
ppm.fit = ppmlasso(ppm.form, sp.xy = sub.euc, env.grid = sub.env, sp.scale = 1, n.fits = 20)
diagnose(ppm.fit, which = "smooth", type = "Pearson")
|
Loading required package: spatstat
Loading required package: spatstat.data
Loading required package: nlme
Loading required package: rpart
spatstat 1.59-0 (nickname: 'J'ai omis les oeufs de caille')
For an introduction to spatstat, type 'beginner'
Note: R version 3.4.4 (2018-03-15) is more than 9 months old; we strongly recommend upgrading to the latest version
Calculating species environmental data for variable: FC
Calculating species environmental data for variable: D_MAIN_RDS
Calculating species environmental data for variable: D_URBAN
Calculating species environmental data for variable: RAIN_ANN
Calculating species environmental data for variable: TMP_MAX
Calculating species environmental data for variable: TMP_MIN
[1] "Output saved in the file SpEnvData.RData"
[1] "Output saved in the file TestPPM.RData"
Fitting Models: 1 of 20
Fitting Models: 2 of 20
Fitting Models: 3 of 20
Fitting Models: 4 of 20
Fitting Models: 5 of 20
Fitting Models: 6 of 20
Fitting Models: 7 of 20
Fitting Models: 8 of 20
Fitting Models: 9 of 20
Fitting Models: 10 of 20
Fitting Models: 11 of 20
Fitting Models: 12 of 20
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Fitting Models: 15 of 20
Fitting Models: 16 of 20
Fitting Models: 17 of 20
Fitting Models: 18 of 20
Fitting Models: 19 of 20
Fitting Models: 20 of 20
Model diagnostics (Pearson residuals)
Diagnostics available:
smoothed residual field
range of smoothed field = [-0.07001, 0.05665]
Null standard deviation of smoothed Pearson residual field: 0.02689
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