Log message:
(geography/R-spatstat.linnet) Updated  2.3.0 to 3.1.3

        CHANGES IN spatstat.linnet VERSION 3.1-3

OVERVIEW

    o Minor corrections to help files.

        CHANGES IN spatstat.linnet VERSION 3.1-2

OVERVIEW

    o Minor improvements to help files.

        CHANGES IN spatstat.linnet VERSION 3.1-1

OVERVIEW

    o Minor improvements

SIGNIFICANT USER-VISIBLE CHANGES

    o rhohat.lpp, rhohat.lppm
    New argument 'rule.eps' passed to 'as.mask'.

    o as.linim.default, as.linim.linfun
    New argument 'rule.eps' passed to 'as.mask'.

        CHANGES IN spatstat.linnet VERSION 3.1-0

OVERVIEW

    o Inhomogeneous K and pcf using automatic estimation of intensity.

    o density.lpp accepts bandwidth selection rules.

    o density.lpp accepts sigma=NULL and has a simple default.

    o Updated package documentation.

SIGNIFICANT USER-VISIBLE CHANGES

    o linearKinhom, linearpcfinhom, linearKEuclidInhom, linearpcfEuclidInhom
    Argument 'lambda=NULL' is now interpreted to mean that the intensity
    should be estimated by kernel smoothing. A warning is issued that this
    is different from the previous behaviour.

    o linearKdot.inhom, linearpcfdot.inhom
    Argument 'lambdaI=NULL' or 'lambdadot=NULL' is now interpreted to mean
    that the intensity should be estimated by kernel smoothing.

    o linearKcross.inhom, linearpcfcross.inhom
    Argument 'lambdaI=NULL' or 'lambdaJ=NULL' is now interpreted to mean
    that the intensity should be estimated by kernel smoothing.

    o density.lpp
    Argument 'sigma' can now be a function in the R language,
    assumed to provide a bandwidth selection rule. This function
    will be applied to the point pattern x to compute the bandwidth.

    o density.lpp
    Argument 'sigma=NULL' is now accepted. The default value is one-eighth
    of the length of the shortest side of the bounding box of x.

    o densityQuick.lpp
    Argument 'X' changed to 'x' for consistency.

    o linearpcfinhom
    New arguments 'adjust.sigma', 'bw' and 'adjust.bw'.

    o linearpcfdot.inhom, linearpcfcross.inhom
    New arguments 'adjust.sigma', 'bw' and 'adjust.bw'.

    o linearpcfEuclidInhom
    New arguments 'adjust.sigma', 'bw' and 'adjust.bw'.

        CHANGES IN spatstat.linnet VERSION 3.0-6

OVERVIEW

    o Internal improvements and bug fixes.

        CHANGES IN spatstat.linnet VERSION 3.0-5

OVERVIEW

    o Improvements and bug fixes in 'lppm' class.

    o Minor extension to random generators.

SIGNIFICANT USER-VISIBLE CHANGES

    o runiflpp, rpoislpp
    The simulation parameters can be determined from an example
    point pattern, given as the argument 'ex'.

    o print.lppm, summary.lppm
    The name of the original point pattern dataset (to which the
    model was fitted) is now printed.

    o print.lppm, summary.lppm
    Improved output.

    o update.lppm
    Internal improvements.

        CHANGES IN spatstat.linnet VERSION 3.0-4

OVERVIEW

    o quantile function on a network.

    o Minor enhancements and bug fixes.

NEW FUNCTIONS

    o quantilefun.linim
    Quantile function, returned as a function.
    Method for 'quantilefun' for images on a network.

BUG FIXES

    o relrisk.lpp
    Crashed if allow.infinite=FALSE.
    Fixed.

        CHANGES IN spatstat.linnet VERSION 3.0-3

OVERVIEW

    o We thank Brian Ripley for contributions.

    o Internal bug fix.

BUG FIXES

    o pairdist.lpp
    Results could have been completely incorrect, due to an internal bug,
    if the linear network data was in the non-sparse representation.

        CHANGES IN spatstat.linnet VERSION 3.0-2

OVERVIEW

    o Internal tweaks to satisfy package checker.

        CHANGES IN spatstat.linnet VERSION 3.0-1

OVERVIEW

    o Internal improvements.

        CHANGES IN spatstat.linnet VERSION 3.0-0

OVERVIEW

    o We thank Greg McSwiggan, Fernando Milesi, Mehdi Moradi, Gopalan Nair
    and James Pope for contributions.

    o spatstat.linnet now depends on the new packages 'spatstat.explore'
    and 'spatstat.model' rather than the old 'spatstat.core'.

    o Kernel smoothing on a linear network.

    o K function and pair correlation function based on Euclidean distance.

    o Inhomogeneous J function on a network.

    o Terminal vertices of a network.

    o Points along a network can be drawn as cross-ticks.

    o Marks attached to vertices and segments of a network.

    o Important change to K function and pair correlation function
    when 'ratio=TRUE'.

    o U-shaped curves in 'rhohat'.

    o Faster computation of the length of the disc in the shortest path metric.

    o Minor improvements and bug fixes.

    o Improvements to internal code.

    o Minor internal changes to package information.

NEW FUNCTIONS

    o lineardisclength
    Compute the length of the disc in the shortest-path metric.

    o marks.linnet, marks<-.linnet
    Marks attached to the vertices and segments of a linear network.

    o Smooth.lpp
    Kernel smoothing (Nadaraya-Watson) on a linear network.

    o distmap.lpp
    Distance map for a point pattern on a network.

    o linearKEuclid, linearpcfEuclid, linearKEuclidInhom, linearpcfEuclidInhom
    K function and pair correlation function based on Euclidean distances.

    o linearJinhom
    Inhomogeneous J function on a linear network.

    o terminalvertices
    Extract the terminal vertices of a linear network.

    o bw.relrisk.lpp
    This function replaces 'bw.relrisklpp'
    and is a method for the generic 'bw.relrisk'.

    o rThomaslpp
    Simulate Thomas cluster process on a network.

SIGNIFICANT USER-VISIBLE CHANGES

    o Package dependence
    'spatstat.linnet' now depends on the new packages 'spatstat.explore'
    and 'spatstat.model' rather than the old 'spatstat.core'.

    o plot.lpp
    If 'shape="crossticks"', the points will be drawn as
    short line segments perpendicular to the network.

    o linearK, linearpcf, linearKdot, linearKcross, linearpcfcross, linearpcfdot
    When 'ratio=TRUE', the denominator is now equal to the number of
    ordered pairs of data points considered. This does not affect the
    summary function, but it changes the calculation of pooled estimates.

    o densityQuick.lpp
    If 'sigma' is a function for selecting a bandwidth,
    additional arguments '...' of densityQuick.lpp will be passed to 'sigma',
    provided they match the name of a formal argument of 'sigma'.

    o bw.relrisklpp
    This function is now deprecated, and is replaced by 'bw.relrisk.lpp',
    a method for the generic 'bw.relrisk'.

    o bw.relrisk.lpp
    When 'method="likelihood"', the cross-validation criterion
    is now defined as the *negative* likelihood. This is consistent with
    'bw.relrisk.ppp', and ensures that the optimum bandwidth is always
    found by minimising the cross-validation criterion.

    o integral.linim, integral.linfun
    New argument 'weight' specifies a weight function for the integration.

    o rhohat.lpp, rhohat.lppm
    New options 'smoother="mountain"' and 'smoother="valley"'
    for estimating a unimodal function (U-shaped curve).

    o rhohat.lpp, rhohat.lppm
    If the covariate is a 'distfun' on a network, the unit of length
    will be saved, and will be displayed on the plot.

    o rhohat.lpp, rhohat.lppm
    New arguments 'jitter', 'jitterfactor', 'interpolate' allow greater
    control over the calculation.

    o plot.linnet
    Optionally displays the marks of the segments or marks of the vertices.
    Changed argument list.

    o print.linnet, summary.linnet
    These functions print information about marks of the segments or vertices.

    o predict.lppm
    Can now compute standard errors.

    o predict.lppm
    New formal arguments 'covariates' and 'se'.

    o rhohat.lpp, rhohat.lppm
    New argument 'do.CI' specifies whether to calculate confidence bands.

BUG FIXES

    o density.lpp
    If 'weights' were given, the results were completely incorrect
    when leaveoneout=TRUE (the default) and at="points".

    o spatstat.model::effectfun
    Results were sometimes incorrect for 'lppm' objects.
    [Spotted by Fernando A. Milesi]
    Fixed.

    o predict.lppm
    Ignored argument 'covariates'.
    Fixed.

    o rhohat.lpp, rhohat.lppm
    The argument 'subset' was not handled correctly in the internal data.
    The estimated function 'rho' was correct
    but the results of 'predict.rhohat' may have been incorrect
    and were computed only on the 'subset'.
    Fixed.

    o plot.lpp
    Did not display the main title in some cases.
    Fixed.

    o "[.lpp", "[.linnet"
    Ignored marks attached to the network segments.
    Fixed.

    o "[.lpp", "[.linnet"
    Crashed if the network vertices had marks, when 'snip=TRUE'.
    Fixed.

    o densityQuick.lpp
    Crashed sometimes with a message about unequal lengths of vectors.
    Fixed.

        CHANGES IN spatstat.linnet VERSION 2.3-2

OVERVIEW

    o 'spatstat.linnet' now depends on 'spatstat.random'.

SIGNIFICANT USER-VISIBLE CHANGES

    o package dependence
    'spatstat.linnet' now depends on the new package 'spatstat.random'.

        CHANGES IN spatstat.linnet VERSION 2.3-1

OVERVIEW

    o More control over resolution of 'linim' objects.

    o Improved documentation.

    o Minor improvements and bug fixes.

SIGNIFICANT USER-VISIBLE CHANGES

    o as.linim.default, as.linim.linfun
    New argument 'nd'

    o integral.linfun
    New argument 'nd'

    o rjitterlpp, rjitter.lpp
    The function 'rjitterlpp' has been renamed 'rjitter.lpp'
    and is now a method for the generic 'rjitter'.

    o rjitterlpp
    This function still exists, but is now deprecated in favour of 'rjitter.lpp'.

BUG FIXES

    o rjitterlpp
    The argument 'radius' was interpreted as a fraction of segment length
    rather than an absolute distance.
    Fixed.

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Log message:
(geography/R-spatstat.linnet) import R-spatstat.linnet-2.3.0

Defines types of spatial data on a linear network and provides
functionality for geometrical operations, data analysis and modelling
of data on a linear network, in the 'spatstat' family of packages.
Contains definitions and support for linear networks, including
creation of networks, geometrical measurements, topological
connectivity, geometrical operations such as inserting and deleting
vertices, intersecting a network with another object, and interactive
editing of networks. Data types defined on a network include point
patterns, pixel images, functions, and tessellations. Exploratory
methods include kernel estimation of intensity on a network,
K-functions and pair correlation functions on a network, simulation
envelopes, nearest neighbour distance and empty space distance,
relative risk estimation with cross-validated bandwidth selection.
Formal hypothesis tests of random pattern (chi-squared,
Kolmogorov-Smirnov, Monte Carlo, Diggle-Cressie-Loosmore-Ford,
Dao-Genton, two-stage Monte Carlo) and tests for covariate effects
(Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov, ANOVA) are also
supported. Parametric models can be fitted to point pattern data using
the function lppm() similar to glm(). Only Poisson models are
implemented so far. Models may involve dependence on covariates and
dependence on marks. Models are fitted by maximum likelihood. Fitted
point process models can be simulated, automatically. Formal
hypothesis tests of a fitted model are supported (likelihood ratio
test, analysis of deviance, Monte Carlo tests) along with basic tools
for model selection (stepwise(), AIC()) and variable selection (sdr).
Tools for validating the fitted model include simulation envelopes,
residuals, residual plots and Q-Q plots, leverage and influence
diagnostics, partial residuals, and added variable plots. Random point
patterns on a network can be generated using a variety of models.