NEWS

---

spatstat.model 3.3-1.002

OVERVIEW

• Tweaks to documentation.
• Minor improvements.

SIGNIFICANT USER-VISIBLE CHANGES

• plot.palmdiag Improved placement of legend.

spatstat.model 3.3-1 (2024-07-15)

OVERVIEW

• Internal changes to satisfy CRAN package checker.

spatstat.model 3.3-0

OVERVIEW

• Package now depends on 'spatstat.univar'.
• Easier control over quadrature schemes.
• More options in fitted.slrm
• Bug fix in predict.ppm.
• Internal improvements.

PACKAGE DEPENDENCE

• spatstat.model now depends on the new package 'spatstat.univar'.

SIGNIFICANT USER-VISIBLE CHANGES

• ppm.ppp New argument 'quad.args' is a list of arguments passed to 'quadscheme' to control the construction of the quadrature scheme.
• fitted.slrm New argument 'type' allows calculation of fitted probabilities, intensities or link function values.
• fitted.slrm New arguments 'dataonly' and 'leaveoneout' allow calculation of fitted values at the data points only, using leave-one-out calculation if desired.

BUG FIXES

• predict.ppm Argument 'eps' was ignored in many cases. Fixed.

spatstat.model 3.2-11 (2024-03-22)

OVERVIEW

• Slightly accelerated.

SIGNIFICANT USER-VISIBLE CHANGES

• spatstat.model package Some computations slightly accelerated.

spatstat.model 3.2-10 (2024-02-02)

OVERVIEW

• Internal bug fix.

spatstat.model 3.2-9

OVERVIEW

• We thank Marta Luraschi for contributions.
• Minor improvements and bug fixes.

SIGNIFICANT USER-VISIBLE CHANGES

• vcov.kppm If any quadrature points have NA values for one of the covariates, these quadrature points are ignored in the variance calculation, with a warning.
• vcov.kppm Minor change to formal arguments.
• vcov.ppm Minor change to formal arguments.

BUG FIXES

• vcov.kppm If any quadrature points had NA values for one of the covariates, the result was a matrix of NA values. Fixed.

spatstat.model 3.2-8 (2023-10-23)

OVERVIEW

• spatstat.model no longer suggests package 'maptools' or 'RandomFields'.
• code for fitting log-Gaussian Cox models has changed.
• minor improvements to help files.

SIGNIFICANT USER-VISIBLE CHANGES

• kppm The code for fitting log-Gaussian Cox process models (clusters="LGCP") has been re-implemented without using the package 'RandomFields'. The current code supports the 'exponential', 'gauss', 'stable', 'gencauchy' and 'matern' covariance models.
• lgcp.estK, lgcp.estpcf This code for fitting log-Gaussian Cox process models has been re-implemented without using the package 'RandomFields'. The current code supports the 'exponential', 'gauss', 'stable', 'gencauchy' and 'matern' covariance models.
• simulate.kppm For log-Gaussian Cox process models (clusters='LGCP') the simulation algorithm has been completely re-implemented to avoid dependence on the defunct package 'RandomFields'. For details, see the help for 'rLGCP' in the package 'spatstat.random'.

spatstat.model 3.2-6 (2023-09-07)

OVERVIEW

• Internal improvements.

SIGNIFICANT USER-VISIBLE CHANGES

• ppm Internal changes to support improvements in spatstat.linnet::lppm.

spatstat.model 3.2-4 (2023-05-15)

OVERVIEW

• Minor improvements.

SIGNIFICANT USER-VISIBLE CHANGES

• cdf.test.ppm Recognises argument 'rule.eps' passed to 'as.mask'.
• dfbetas.ppm Recognises argument 'rule.eps' passed to 'as.mask'.
• leverage.ppm Recognises argument 'rule.eps' passed to 'as.mask'.
• rhohat.ppm New argument 'rule.eps' passed to 'as.mask'.

spatstat.model 3.2-3 (2023-04-21)

OVERVIEW

• Tweak to satisfy package checker.

spatstat.model 3.2-2

OVERVIEW

• Accelerated some code.
• Standard errors are now available for 'ppm' models fitted using 'gam'.
• Internal reorganisation.
• Minor changes to documentation.
• Bug fixes.

SIGNIFICANT USER-VISIBLE CHANGES

• plot.mppm New argument 'main'.

BUG FIXES

• predict.ppm Standard error calculation ('se=TRUE') crashed if the fitted model was a generalised additive model (fitted with 'use.gam=TRUE'). Fixed.
• effectfun Standard error calculation ('se.fit=TRUE') crashed if the fitted model was a generalised additive model (fitted with 'use.gam=TRUE'). Fixed.
• parres If 'model' was a large object, computation was extremely slow or terminated with a message about 'deparse'. Fixed.
• plot.mppm If the fitted model 'x' was a large object, computation was extremely slow or terminated with a message about 'deparse'. Fixed.
• predict.ppm If 'new.coef' was given and the fitted model 'object' was a large object, computation was extremely slow, or terminated with message about 'deparse'. Fixed.

spatstat.model 3.2-1 (2023-02-15)

OVERVIEW

• Minor changes to citation file, to satisfy CRAN.

spatstat.model 3.2-0

OVERVIEW

• Improvements to 'update' methods for point process models.
• New 'update' methods for classes 'dppm' and 'rppm'.
• Minor improvements and bug fixes.

NEW FUNCTIONS

• update.dppm Update method for determinantal point process models.
• update.rppm Update method for recursively partitioned point process models.

SIGNIFICANT USER-VISIBLE CHANGES

• update.slrm Now accepts the idiom 'update(object, X)' where X is a point pattern.
• update.ppm, update.kppm, update.dppm, update.slrm, update.rppm All of these methods now accept the idiom 'update(object, X)' where X is a point pattern.
• print.ppm, summary.ppm Prints the name of the point pattern dataset to which the model was fitted.
• update.ppm Internal improvements.

spatstat.model 3.1-2 (2023-01-26)

OVERVIEW

• Minor changes to satisfy CRAN package checker.

spatstat.model 3.1-1

OVERVIEW

• We thank Bethany Macdonald for contributions.
• kppm has been accelerated when method='palm' or 'clik2'
• kppm can save the history of the optimisation algorithm.
• Bug fixes and internal tweaks.

SIGNIFICANT USER-VISIBLE CHANGES

• kppm New argument 'trajectory' specifies whether to save the history of function evaluations performed by the optimization algorithm.
• kppm Computation accelerated when 'method="palm"' or 'method='clik2'". [Kindly contributed by Bethany Macdonald.]

BUG FIXES

• simulate.kppm If the model was very close to a Poisson process, and if saveLambda=TRUE was selected, the attribute "Lambda" was incorrectly labelled "lambda". Fixed.
• simulate.kppm Simulation of the variance-gamma model terminated with an error about the value of 'nu' (with recent versions of spatstat.random). Fixed.
• kppm Terminated with an error about missing argument 'A', if penalised=TRUE. Fixed.
• summary.kppm Did not correctly recognise when a model was fitted using a penalty. Fixed.

spatstat.model 3.1-0

OVERVIEW

• We thank Tilman Davies and Martin Hazelton for contributions.
• Penalised model-fitting for Neyman-Scott cluster process models.
• Index of the strength of clustering in a Neyman-Scott cluster process model.
• Probability of having any siblings.
• More information is printed about Neyman-Scott cluster process models.
• Minor improvements.

NEW CLASSES

• traj Trajectory (history of function evaluations) in a model that was fitted by optimisation.

NEW FUNCTIONS

• panysib Probability that a point in a cluster process has any siblings.
• is.poissonclusterprocess Detects whether a given model is a Poisson cluster process (which includes Neyman-Scott processes).
• traj, print.traj, plot.traj, lines.traj Extract, print and plot the trajectory of function evaluations.

SIGNIFICANT USER-VISIBLE CHANGES

• kppm New argument 'penalised' supports penalised model-fitting with a penalty against extremely large or small values of the cluster scale.
• print.kppm, summary.kppm Additional characteristics of the fitted model are reported, including the cluster strength 'phi' and the sibling probability.
• varcount New argument 'relative' (supports calculation of the overdispersion index).
• plot.palmdiag Improved calculation of y axis limits.

spatstat.model 3.0-3

OVERVIEW

• Palm intensity diagnostic.

NEW FUNCTIONS

• palmdiagnose, plot.palmdiag Palm intensity diagnostic plot for cluster process models proposed by Tanaka, Ogata and Stoyan.

spatstat.model 3.0-2 (2022-11-07)

OVERVIEW

• Minor changes to placate the package checker.

spatstat.model 3.0-1

OVERVIEW

• Minor changes to placate the package checker.

spatstat.model 3.0-0

OVERVIEW

• New package
• We thank Achmad Choiruddin and Suman Rakshit for contributions.
• Regularized model-fitting in 'ppm' and 'kppm'.
• integral.msr accepts a weight function.
• Weighted version of a measure.
• Residuals for recursively-partitioned models.
• Residuals for any estimate of intensity.
• U-shaped curves in 'rhohat'.
• Bug fixes and minor improvements.

NEW FUNCTIONS

• measureWeighted Weighted version of a measure.
• residuals.rppm Residual measure for a recursively-partitioned point process model.
• residualMeasure Residual measure given an observed point pattern and an estimate of its intensity.

SIGNIFICANT USER-VISIBLE CHANGES

• Package structure The package 'spatstat.core' has been split into two packages called 'spatstat.explore' (for exploratory data analysis) and 'spatstat.model' (for modelling and formal inference).
• spatstat.model The new package 'spatstat.model' contains the code for model-fitting, model diagnostics, and formal inference. Examples include 'ppm', 'kppm', 'mppm', 'dppm', 'slrm', 'simulate.ppm', 'anova.ppm', 'diagnose.ppm', 'residuals.ppm', 'leverage.ppm', 'addvar', 'parres',
• NEWS The NEWS file for the new package 'spatstat.model' contains older news items from the defunct package 'spatstat.core' (for functions which are now in 'spatstat.model').
• ppm New argument 'improve.type'.
• ppm Now supports regularized model-fitting when 'improve.type="enet"'.
• ppm Option 'method="ho"' is replaced by 'improve.type="ho"'.
• ppm Huang-Ogata approximate maximum likelihood can be applied to logistic fits by setting 'method="logi"' and 'improve.type="ho"'.
• kppm New argument 'ppm.improve.type'.
• kppm Now supports regularized model-fitting of the first order trend when 'ppm.improve.type="enet"'.
• integral.msr New argument 'weight' specifies a weight (integrand) for the integration.
• rhohat.ppm, rhohat.slrm New options 'smoother="mountain"' and 'smoother="valley"' for estimating a unimodal function (U-shaped curve).
• rhohat.ppm, rhohat.slrm If the unit of length is a 'distfun', the name of the unit of length is saved and displayed on the plot.
• rhohat.ppm, rhohat.slrm New arguments 'jitter', 'jitterfactor', 'interpolate' allow greater control over the calculation.
• rhohat.ppm, rhohat.slrm New argument 'do.CI' specifies whether to calculate confidence bands.

BUG FIXES

• predict.ppm Argument 'new.coef' was ignored in the calculation of the standard error when 'se=TRUE'. Fixed.
• predict.ppm Argument 'new.coef' was ignored in calculating the standard error (and therefore the width of the interval) when 'type="count"' and 'interval="confidence"' or 'interval="prediction"'. Fixed.
• vcov.mppm Crashed with a message about 'subscript out of bounds', for some models. Fixed.

spatstat.model 2.4-4.010

OVERVIEW

• Internal improvements.

spatstat.model 2.4-4

OVERVIEW

• Bug fixes and minor improvements.

spatstat.model 2.4-3

OVERVIEW

• We thank Art Stock for contributions.
• Bug fixes and minor improvements.

spatstat.model 2.4-2

OVERVIEW

• Internal bug fixes.

spatstat.model 2.4-1

OVERVIEW

• We thank Frederic Lavancier, Sebastian Meyer and Sven Wagner for contributions.
• Improved approximation of intensity of Gibbs models.
• Experimental code to represent (theoretical) point process models
• Extract more information about a point process model.
• Internal improvements and bug fixes.

NEW CLASSES

• zgibbsmodel Experimental. An object of class 'zgibbsmodel' represents a Gibbs point process model with specified parameter values (whereas 'ppm' represents a model fitted to data).

NEW FUNCTIONS

• hardcoredist Extract the hard core distance of a point process model.
• interactionorder Extract the order of interpoint interaction of a point process model.
• zgibbsmodel Experimental. Create an object of class 'zgibbsmodel'.
• print.zgibbsmodel Experimental. Print an object of class 'zgibbsmodel'.
• is.poisson.zgibbsmodel, is.stationary.zgibbsmodel Experimental. Methods for class 'zgibbsmodel'

SIGNIFICANT USER-VISIBLE CHANGES

• intensity.ppm Can now calculate the Coeurjolly-Lavancier DPP approximation of intensity. [Code kindly contributed by Frederic Lavancier] New argument 'approx' specifies the choice of approximation.

BUG FIXES

• vcov.ppm Crashed in some cases, with message 'object lamdel not found'. [Spotted by Sven Wagner.] Fixed.

spatstat.model 2.4-0

OVERVIEW

• We thank Sriram Ramamurthy for contributions.
• spatstat.core now depends on the new package 'spatstat.random'.
• Functions for generating random patterns have been removed.
• Important bug fixes in anova.mppm and vcov.mppm.
• Minor improvements and bug fixes

SIGNIFICANT USER-VISIBLE CHANGES

• package structure The code for generating random spatial patterns (including 'rpoispp', 'rMatClust', 'rThomas', 'rNeymanScott', 'rStrauss', 'rmh') has been removed from 'spatstat.core' and placed in a new package 'spatstat.random'. This new package is required by 'spatstat.core'.
• anova.mppm Improved labelling of models in output.
• qqplot.ppm, plot.qqppm Improved the text label indicating the type of residuals.

BUG FIXES

• vcov.mppm For Gibbs (non-Poisson) models, the variance matrix was calculated incorrectly in some cases. Fixed.
• anova.mppm Results were sometimes incorrect if the two models had different interactions (e.g. Strauss vs Poisson). Fixed.
• anova.mppm Crashed for some models with a message about 'coefficient missing from new.coef'. Fixed.
• anova.mppm Gave a warning for some models about "Internal error: unable to map submodels to full model". Fixed.
• addvar If the covariate contained NA, NaN or Infinite values, the calculations were sometimes incorrect. Fixed.
• pcfmodel.ppm Refused to handle an inhomogeneous Poisson process. Fixed.
• fitted.ppm Crashed if leaveoneout=TRUE and the model had no fitted coefficients. Fixed.

spatstat.model 2.3-2

OVERVIEW

• More diagnostics for spatial logistic regression models.
• Important bug fix in kppm.
• Increased numerical stability in kppm.
• Minor improvements and bug fixes.
• We thank Jonas Brehmer for contributions.

NEW FUNCTIONS

• lurking.slrm Lurking variable plot for spatial logistic regression models.
• eem.slrm Exponential energy marks for spatial logistic regression models.
• eem.ppm Exponential energy marks for Gibbs and Poisson point process models (this function was previously called 'eem').

SIGNIFICANT USER-VISIBLE CHANGES

• eem The function 'eem' is now generic, with methods for 'ppm' and 'slrm'. The function previously named 'eem' is now called 'eem.ppm'.
• objsurf.dppm, objsurf.kppm, objsurf.mincontrast New arguments 'xlim', 'ylim' determine the range of parameter values to be considered.
• Hybrid Printed output from hybrid models has been improved slightly.
• kppm New default settings ensure greater numerical stability of the optimization algorithm against the effects of the scale of the spatial coordinates. New argument 'stabilize' specifies whether the optimization algorithm should be numerically stabilized.
• pcf Improved error message

BUG FIXES

• kppm Results were sometimes incorrect for method='clik2' and method='palm' because the log composite likelihood was erroneously truncated to positive values. Any fitted model for which logLik(model) = 2.2e-16 should be suspected of being incorrect. Fixed.
• MultiHard A hybrid of 'MultiHard' with another multitype interaction caused an error. Fixed.
• simulate.dppm, simulate.detpointprocfamily Crashed, rarely, with error message 'The dimension differs from the number of columns in index'. Fixed.
• as.fv.kppm, as.fv.dppm The default plot labels in 'as.fv(x)' implied that the model 'x' was inhomogeneous. Fixed.

spatstat.model 2.3-1

OVERVIEW

• Covariates in ppm and mppm may be functions that depend on the marks as well as the spatial coordinates.
• Automatic selection of threshold for defining a binary predictor.
• Random perturbation of line segments.
• Minor extensions, performance improvements, and bug fixes.

NEW FUNCTIONS

• coef<-.fii Changes the coefficients of a fitted interaction object (a method for the generic "coef<-")

SIGNIFICANT USER-VISIBLE CHANGES

• ppm Covariates which are functions may now depend on the marks as well as the spatial coordinates: function(x,y,marks).
• mppm Covariates which are functions may now depend on the marks as well as the spatial coordinates: function(x,y,marks).
• reach.kppm Now returns a result for LGCP models as well as cluster models.
• update.kppm New argument 'envir'.
• clusterfit Minor changes to the argument list.
• mincontrast Minor changes to the argument list.
• mincontrast Improved algorithm for handling NA, NaN or infinite values.
• varcount Argument B has a sensible default.

BUG FIXES

• subfits The fitted interaction coefficients were garbled. If 'mfit' is the mppm object and 'a <- subfits(mfit)[[i]]' is one of the sub-models, then coef(a) was correct, but coef(fitin(a)) was incorrect. The fitted interaction was shown correctly by printing 'mfit' but incorrectly by printing 'a'. Fixed.
• varcount The result was very inaccurate if the cluster radius was small compared to the size of the window 'B', due to discretisation error. Fixed.

spatstat.model 2.3-0

OVERVIEW

• We thank Chiara Fend for contributions.
• Extensive support for spatial logistic regression models.
• New fitting method in kppm and dppm.
• Summary method for 'objsurf'.
• Minor bug fixes.

NEW FUNCTIONS

• response Generic function which extracts the values of the response in a fitted model. There are methods for lm, glm (which extract the numeric vector of responses), and ppm, kppm, slrm, lppm and mppm (which extract the original data point pattern).
• summary.objsurf, print.summary.objsurf Summary method for 'objsurf'
• residuals.slrm Residuals for spatial logistic regression models.
• leverage.slrm, influence.slrm, dfbetas.slrm, dffit.slrm Leverage and influence diagnostics for spatial logistic regression models.
• rhohat.slrm Method for 'rhohat' for spatial logistic regression models.
• envelope.slrm Method for 'envelope' for spatial logistic regression models.
• intensity.slrm Method for 'intensity' for spatial logistic regression models.
• deviance.slrm Method for 'deviance' for spatial logistic regression models.
• pseudoR2.slrm Method for 'pseudoR2' for spatial logistic regression models.
• quadrat.test.slrm Method for 'quadrat.test' for spatial logistic regression models.
• parameters.slrm Method for 'parameters' for spatial logistic regression models.
• valid.slrm Method for 'valid' for spatial logistic regression models.
• emend.slrm Method for 'emend' for spatial logistic regression models.
• roc.slrm Method for 'roc' for spatial logistic regression models.
• auc.slrm Method for 'auc' for spatial logistic regression models.
• Window.slrm, as.owin.slrm Methods for 'Window' and 'as.owin' for spatial logistic regression models.

SIGNIFICANT USER-VISIBLE CHANGES

• kppm, dppm New option 'method="adapcl"' performs adaptive composite likelihood fitting. [Contributed by Chiara Fend.]

BUG FIXES

• clusterfield Values of the cluster field were slightly incorrect (slightly higher than the correct values) near the edge of the window, because an 'edge correction' was mistakenly applied. Fixed.

spatstat.model 2.2-0

OVERVIEW

• summary method for spatial logistic regression models

NEW FUNCTIONS

• summary.slrm, print.summary.slrm Summary method for spatial logistic regression models
• coef.summary.slrm Print the fitted coefficients, confidence interval and p-values for a spatial logistic regression model.

spatstat.model 2.1-2

OVERVIEW

• Reduced CRAN check time.

spatstat.model 2.1-1

OVERVIEW

• Minor bug fix

BUG FIXES

• simulate.kppm Conditional simulation crashed on rare occasions, with an error about negative probabilities. Fixed.

spatstat.model 2.1-0

OVERVIEW

• We thank Achmad Choiruddin, Jean-Francois Coeurjolly and Rasmus Waagepetersen for contributions.
• Conditional simulation in kppm
• Information criteria for model selection in kppm
• Modified handling of covariates in slrm
• Improved output in summary.mppm
• Minor improvements and bug fixes.

NEW FUNCTIONS

• ic Information criteria for model selection in ppm and kppm. Kindly contributed by Achmad Choiruddin, Jean-Francois Coeurjolly and Rasmus Waagepetersen.

SIGNIFICANT USER-VISIBLE CHANGES

• simulate.kppm Conditional simulation of the model, given a fixed number of points, is now supported using the new arguments 'n.cond' and 'w.cond'.
• slrm In the default case (where dataAtPoints is not given) all spatial covariates, including the spatial coordinates x and y, are now evaluated at the centre of each pixel. This improves consistency with other implementations of spatial logistic regression.
• slrm Silently ignores any arguments '...' that are not recognised by 'as.mask'
• summary.mppm Improved summary of the dependence of the interpoint interaction on the covariates.
• pairs.im New argument 'drop'.

BUG FIXES

• model.matrix.mppm If the model was fitted using 'gam', the resulting matrix did not have an 'assign' attribute. Fixed.
• model.depends Crashed for models fitted using 'gam'. Fixed.
• predict.slrm, fitted.slrm Crashed if the model was fitted using split pixels (argument 'splitby'). Fixed.
• predict.slrm, fitted.slrm Crashed in some cases when 'window' was given. Fixed.
• update.slrm Failed to find covariates that were provided in 'env'. Fixed.

spatstat.model 2.0-0

OVERVIEW

• We thank Corey Anderson, Michael Chirico, Andy Craig, Marcelino de la Cruz, Tilman Davies, Pavel Fibich, Kurt Hornik, Gopalan Nair, Yonatan Rosen and Rasmus Waagepetersen for contributions.
• More support for spatial logistic regression models.
• predict.mppm now works for multitype point process models.
• Improved handling of 'newdata' in predict.mppm.
• More support for multi-dimensional patterns.

SIGNIFICANT USER-VISIBLE CHANGES

• slrm 'step' can now be applied to models fitted using 'slrm'.
• predict.mppm Now supports multitype point process models.
• predict.mppm Improved handling of argument 'newdata'
• simulate.ppm Now recognises the argument 'window' as an alternative to 'w'.
• kppm Improved numerical robustness.
• anova.mppm Issues a warning when applied to random-effects models (models fitted using the argument 'random').
• mincontrast New argument 'action.bad.values' specifies what action is taken when the summary function produces NA or NaN or infinite values.

BUG FIXES

• rMatClust, rThomas, rCauchy, rVarGamma If the fitted model was effectively a Poisson process, the result did not have attributes 'Lambda' and 'parents' even when the user requested them. Fixed.
• model.matrix.mppm Crashed with random-effects models. Fixed.
• anova.mppm Crashed with random-effects models. Fixed.
• objsurf.kppm Crashed if the model was fitted by Palm likelihood (method="palm") or second order composite likelihood (method="clik2"). Fixed.

spatstat.model 1.65-11

OVERVIEW

• Internal tweaks.

spatstat.model 1.65-10

OVERVIEW

• Minor corrections to documentation.

spatstat.model 1.65-9

OVERVIEW

• We thank Ian Buller for a suggestion.

spatstat.model 1.65-8

OVERVIEW

• Minor changes to appease the compiler.

spatstat.model 1.65-7

OVERVIEW

• We thank Michael Chirico for a contribution.
• Minor changes to appease the compiler.

spatstat.model 1.65-6

OVERVIEW

• We thank Tilman Davies and Pavel Fibich for contributions.
• Important bug fix in simulation of log-Gaussian Cox processes.
• Increased speed for large datasets.
• variance calculations handle larger datasets.

SIGNIFICANT USER-VISIBLE CHANGES

• vcov.ppm, summary.ppm Variance calculations now handle larger datasets (using sparse arrays).
• overall speed Changes have been made to the internal code of spatstat which should accelerate computations involving large datasets.
• localpcf, localpcfinhom New argument 'rvalue'.

BUG FIXES

• simulate.kppm Simulation results for log-Gaussian Cox processes were incorrect unless the pixel dimensions and pixel spacings were identical on the horizontal and vertical axes. (If pixel dimensions were not specified, then the results were incorrect whenever the Frame of the simulation window was not a square.) [Spotted by Tilman Davies.] Fixed.
• print.ppm Crashed sometimes when applied to the result of subfits(). Fixed.

spatstat.model 1.65-5

OVERVIEW

• Minor changes required by CRAN.

spatstat.model 1.65-1

OVERVIEW

• Added NEWS file.

spatstat.model 1.65-0

OVERVIEW

• Package initialised at version 1.65-0

SIGNIFICANT USER-VISIBLE CHANGES

• spatstat.core The package 'spatstat.core' has been created from a subset of the code in the original 'spatstat' package version 1.65-0. It contains the core functionality for statistical analysis of spatial data. For an overview, see help("spatstat.core-package")
• Execution The 'spatstat.core' package is slightly faster than the corresponding code in the 'spatstat' package, because the procedure for calling internal C functions has been streamlined.