revised plotting functions (caution: new arguments defining line widths, etc.)
scale of the dist2V variable is now supported
added argument "other arguments" to intensity_pspline for compatibility with older versions
revised summary for gnppfit objects
geonet version 0.5.0 (Github release)
new function network_ISE for the computation of integrated squared errors
new function network_integral for the computation of an integral of the intensity
geonet supplies wrappers for density.lpp, i.e. the intensity on a geometric network can be
estimated by employing kernel based methods
fixed bug which occurs if a smooth covariate is specified in formula after a linear covariate
geonet version 0.4.0 (Github release)
summaries and related print methods now also print information on the
linear network representation
default penalty is now of order r = 2
the global knot distance delta can now be supplied as a quantile of the curve
lengths of the network and the global bin width h as a fraction of the global
knot distance
fixed bug in as_gnpp.lpp when linear point pattern is not marked
fixed bug in runif_gn
added function rgnpp which allows to simulate from a fitted intensity
geonet version 0.3.0 (Github release)
algorithm options can now be supplied to intensity_pspline via the
"control" argument
as_gn now also takes the "units" attribute from a linnet object
added missing summary and print methods
fixed bug in "internal" occurring when a linear covariates has length 1
internal covariates are recognized automatically and do not need to be
assigned in the formula
geonet version 0.2.0 (GitHub release)
added internal covariate information to the montgomery network
fixed bug in network_penalty occurring when r = 1
model summary has been changed
fit_poisson_model is only doing on Fisher scoring iteration within the inner
loop from the second iteration
effective degrees of freedom is computed for smooth terms
allow for general internal covariates added to the lins attribute of the
network
internal covariate "dist2V" can be added to the linear predictor
stopping criterion now depends on relative difference of theta and not of rho
verbose argument added to intensity_pspline which allows to track the
progress of the fitting algorithm