[pkgsrc/trunk]: pkgsrc/geography geography/R-spatstat: import R-spatstat-1.63.2

[brook <brook%pkgsrc.org@localhost>]

details:   https://anonhg.NetBSD.org/pkgsrc/rev/ecc6d95133bd
branches:  trunk
changeset: 436667:ecc6d95133bd
user:      brook <brook%pkgsrc.org@localhost>
date:      Fri Aug 07 03:55:17 2020 +0000

description:
geography/R-spatstat: import R-spatstat-1.63.2

Comprehensive open-source toolbox for analysing Spatial Point
Patterns. Focused mainly on two-dimensional point patterns, including
multitype/marked points, in any spatial region. Also supports
three-dimensional point patterns, space-time point patterns in any
number of dimensions, point patterns on a linear network, and patterns
of other geometrical objects. Supports spatial covariate data such as
pixel images. Contains over 2000 functions for plotting spatial data,
exploratory data analysis, model-fitting, simulation, spatial
sampling, model diagnostics, and formal inference. Many data types and
exploratory methods are supported.  Formal hypothesis tests of random
pattern and tests for covariate effects are also supported. Parametric
models can be fitted to point pattern data using the functions ppm(),
kppm(), slrm(), dppm() similar to glm(). Types of models include
Poisson, Gibbs and Cox point processes, Neyman-Scott cluster
processes, and determinantal point processes. Models may involve
dependence on covariates, inter-point interaction, cluster formation
and dependence on marks. Models are fitted by maximum likelihood,
logistic regression, minimum contrast, and composite likelihood
methods. A model can be fitted to a list of point patterns (replicated
point pattern data) using the function mppm(). The model can include
random effects and fixed effects depending on the experimental design,
in addition to all the features listed above.  Fitted point process
models can be simulated, automatically. Formal hypothesis tests of a
fitted model are supported along with basic tools for model selection.

diffstat:

 geography/Makefile            |   3 ++-
 geography/R-spatstat/DESCR    |  24 ++++++++++++++++++++++++
 geography/R-spatstat/Makefile |  22 ++++++++++++++++++++++
 geography/R-spatstat/distinfo |   6 ++++++
 4 files changed, 54 insertions(+), 1 deletions(-)

diffs (81 lines):

diff -r 8e9ce140830d -r ecc6d95133bd geography/Makefile
--- a/geography/Makefile        Fri Aug 07 03:44:52 2020 +0000
+++ b/geography/Makefile        Fri Aug 07 03:55:17 2020 +0000
@@ -1,4 +1,4 @@
-# $NetBSD: Makefile,v 1.88 2020/08/07 03:44:39 brook Exp $
+# $NetBSD: Makefile,v 1.89 2020/08/07 03:55:17 brook Exp $
 #
 
 COMMENT=       Software for geographical-related uses
@@ -11,6 +11,7 @@
 SUBDIR+=       R-maptools
 SUBDIR+=       R-prettymapr
 SUBDIR+=       R-rgeos
+SUBDIR+=       R-spatstat
 SUBDIR+=       R-spatstat.data
 SUBDIR+=       R-spatstat.utils
 SUBDIR+=       cm2gpx
diff -r 8e9ce140830d -r ecc6d95133bd geography/R-spatstat/DESCR
--- /dev/null   Thu Jan 01 00:00:00 1970 +0000
+++ b/geography/R-spatstat/DESCR        Fri Aug 07 03:55:17 2020 +0000
@@ -0,0 +1,24 @@
+Comprehensive open-source toolbox for analysing Spatial Point
+Patterns. Focused mainly on two-dimensional point patterns, including
+multitype/marked points, in any spatial region. Also supports
+three-dimensional point patterns, space-time point patterns in any
+number of dimensions, point patterns on a linear network, and patterns
+of other geometrical objects. Supports spatial covariate data such as
+pixel images. Contains over 2000 functions for plotting spatial data,
+exploratory data analysis, model-fitting, simulation, spatial
+sampling, model diagnostics, and formal inference. Many data types and
+exploratory methods are supported.  Formal hypothesis tests of random
+pattern and tests for covariate effects are also supported. Parametric
+models can be fitted to point pattern data using the functions ppm(),
+kppm(), slrm(), dppm() similar to glm(). Types of models include
+Poisson, Gibbs and Cox point processes, Neyman-Scott cluster
+processes, and determinantal point processes. Models may involve
+dependence on covariates, inter-point interaction, cluster formation
+and dependence on marks. Models are fitted by maximum likelihood,
+logistic regression, minimum contrast, and composite likelihood
+methods. A model can be fitted to a list of point patterns (replicated
+point pattern data) using the function mppm(). The model can include
+random effects and fixed effects depending on the experimental design,
+in addition to all the features listed above.  Fitted point process
+models can be simulated, automatically. Formal hypothesis tests of a
+fitted model are supported along with basic tools for model selection.
diff -r 8e9ce140830d -r ecc6d95133bd geography/R-spatstat/Makefile
--- /dev/null   Thu Jan 01 00:00:00 1970 +0000
+++ b/geography/R-spatstat/Makefile     Fri Aug 07 03:55:17 2020 +0000
@@ -0,0 +1,22 @@
+# $NetBSD: Makefile,v 1.1 2020/08/07 03:55:17 brook Exp $
+
+R_PKGNAME=     spatstat
+R_PKGVER=      1.63-2
+CATEGORIES=    geography
+
+MAINTAINER=    pkgsrc-users%NetBSD.org@localhost
+COMMENT=       Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests
+LICENSE=       gnu-gpl-v2
+
+USE_LANGUAGES+=        c c++
+
+DEPENDS+=      R-deldir>=0.0.21:../../geography/R-deldir
+DEPENDS+=      R-spatstat.data>=1.4.3:../../geography/R-spatstat.data
+DEPENDS+=      R-spatstat.utils>=1.17.0:../../geography/R-spatstat.utils
+DEPENDS+=      R-abind>=1.4.0:../../math/R-abind
+DEPENDS+=      R-goftest>=1.0.3:../../math/R-goftest
+DEPENDS+=      R-polyclip>=1.5.0:../../graphics/R-polyclip
+DEPENDS+=      R-tensor>=1.5:../../math/R-tensor
+
+.include "../../math/R/Makefile.extension"
+.include "../../mk/bsd.pkg.mk"
diff -r 8e9ce140830d -r ecc6d95133bd geography/R-spatstat/distinfo
--- /dev/null   Thu Jan 01 00:00:00 1970 +0000
+++ b/geography/R-spatstat/distinfo     Fri Aug 07 03:55:17 2020 +0000
@@ -0,0 +1,6 @@
+$NetBSD: distinfo,v 1.1 2020/08/07 03:55:17 brook Exp $
+
+SHA1 (R/spatstat_1.63-2.tar.gz) = ad5767ca719e529f3cb37b34bd1cb12c8371ac30
+RMD160 (R/spatstat_1.63-2.tar.gz) = 212c6d53bae938b7f4bce1bc49d936b2fc982f80
+SHA512 (R/spatstat_1.63-2.tar.gz) = 5fe1bf55979a193b8b23e5ddee623638e009e78c2074e9306f4b39b206ccb3a8be00771fb941d47af7843d967fef515fd707b58462825ec6ac2174f43193f1c2
+Size (R/spatstat_1.63-2.tar.gz) = 6715623 bytes