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geography/R-spatstat.linnet,
Linear Networks Functionality of the spatstat Family
Branch: CURRENT,
Version: 3.2.5,
Package name: R-spatstat.linnet-3.2.5,
Maintainer: pkgsrc-usersDefines 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.
Master sites: (Expand)
Version history: (Expand)
- (2025-02-08) Updated to version: R-spatstat.linnet-3.2.5
- (2024-12-01) Updated to version: R-spatstat.linnet-3.2.3
- (2024-01-14) Updated to version: R-spatstat.linnet-3.1.3
- (2021-09-20) Package added to pkgsrc.se, version R-spatstat.linnet-2.3.0 (created)
CVS history: (Expand)
2025-02-08 10:25:44 by Makoto Fujiwara | Files touched by this commit (2) |
Log message:
(geography/R-spatstat.linnet) Updated 3.2.3 to 3.2.5
CHANGES IN spatstat.linnet VERSION 3.2-5
OVERVIEW
o Minor changes in documentation to satisfy the package checker.
CHANGES IN spatstat.linnet VERSION 3.2-4
OVERVIEW
o Bug fix in lppm.
BUG FIXES
o lppm
For models involving covariates of class 'lintess', the internal
structure of the fitted model was corrupted, leading to errors in
calculating properties of the fitted model, such as predict.lppm.
[Spotted by Andrea Gilardi.]
[Bug fix requires spatstat.model 3.3-3.002]
Fixed.
|
2024-12-01 10:43:59 by Makoto Fujiwara | Files touched by this commit (2) |
Log message:
(geography/R-spatstat.linnet) Updated 3.1.3 to 3.2.3
CHANGES IN spatstat.linnet VERSION 3.2-3
OVERVIEW
o Shortest path between two points on a network.
NEW FUNCTIONS
o shortestpath
Find the shortest path between two specified points on a network,
and return it as a line segment pattern.
CHANGES IN spatstat.linnet VERSION 3.2-2
OVERVIEW
o Tweaks to documentation.
o Internal improvements.
CHANGES IN spatstat.linnet VERSION 3.2-1
OVERVIEW
o Internal tweaks to satisfy CRAN package checker.
CHANGES IN spatstat.linnet VERSION 3.2-0
OVERVIEW
o spatstat.linnet now depends on 'spatstat.univar'.
o extract the subset of an image that lies on selected segments of network.
o Minor improvements.
o Internal improvements.
PACKAGE DEPENDENCE
o spatstat.linnet
Now depends on the new package 'spatstat.univar'.
SIGNIFICANT USER-VISIBLE CHANGES
o identify.lpp
Automatically starts a new plot device and displays `x`
if there is no plot device open.
o thinNetwork
X can be a pixel image on a linear network (object of class 'linim').
o plot.linnet, plot.lpp
These functions now recognise the argument 'adj.main'.
CHANGES IN spatstat.linnet VERSION 3.1-5
OVERVIEW
o Slightly accelerated.
o Internal stability improvements.
SIGNIFICANT USER-VISIBLE CHANGES
o spatstat.linnet package
Some computations slightly accelerated.
CHANGES IN spatstat.linnet VERSION 3.1-4
OVERVIEW
o Added a full list of functions to the main help file.
o Intersection of a 2D tessellation with a network.
o Internal improvements.
SIGNIFICANT USER-VISIBLE CHANGES
o intersect.lintess
Can compute the intersection between a two-dimensional tessellation
and a linear network (yielding a tessellation on the network).
|
2024-01-14 03:44:42 by Makoto Fujiwara | Files touched by this commit (2) |  |
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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2021-10-26 12:45:18 by Nia Alarie | Files touched by this commit (108) |
Log message:
geography: Replace RMD160 checksums with BLAKE2s checksums
All checksums have been double-checked against existing RMD160 and
SHA512 hashes
|
2021-10-07 16:09:33 by Nia Alarie | Files touched by this commit (108) |
Log message:
geography: Remove SHA1 hashes for distfiles
|
2021-09-20 12:45:32 by Makoto Fujiwara | Files touched by this commit (3) |
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.
|