
        CHANGES IN spatstat.core VERSION 2.3-0

OVERVIEW

    o We thank Chiara Fend for contributions.
    
    o Extensive support for spatial logistic regression models.

    o New fitting method in kppm and dppm.

    o Transect of an image along a curve.

    o Image cross-correlation and cross-covariance.
    
    o Summary method for 'objsurf'.

    o Minor bug fixes.

NEW FUNCTIONS

    o 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).

    o cov.im, cor.im
    Correlation or covariance between several pixel images.
    
    o summary.objsurf, print.summary.objsurf
    Summary method for 'objsurf'

    o residuals.slrm
    Residuals for spatial logistic regression models.
    
    o leverage.slrm, influence.slrm, dfbetas.slrm, dffit.slrm
    Leverage and influence diagnostics for spatial logistic regression models.
    
    o rhohat.slrm
    Method for 'rhohat' for spatial logistic regression models.

    o envelope.slrm
    Method for 'envelope' for spatial logistic regression models.

    o intensity.slrm
    Method for 'intensity' for spatial logistic regression models.

    o deviance.slrm
    Method for 'deviance' for spatial logistic regression models.

    o pseudoR2.slrm
    Method for 'pseudoR2' for spatial logistic regression models.

    o quadrat.test.slrm
    Method for 'quadrat.test' for spatial logistic regression models.

    o parameters.slrm
    Method for 'parameters' for spatial logistic regression models.

    o valid.slrm
    Method for 'valid' for spatial logistic regression models.

    o emend.slrm
    Method for 'emend' for spatial logistic regression models.

    o roc.slrm
    Method for 'roc' for spatial logistic regression models.

    o auc.slrm
    Method for 'auc' for spatial logistic regression models.

    o Window.slrm, as.owin.slrm
    Methods for 'Window' and 'as.owin' for spatial logistic regression models.

SIGNIFICANT USER-VISIBLE CHANGES

    o kppm, dppm
    New option 'method="adapcl"' performs adaptive composite likelihood fitting.
    [Contributed by Chiara Fend.]
    
    o transect.im
    New argument 'curve' allows the user to specify a curved transect.

BUG FIXES

    o 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.

    o rhohat
    The rug plot (produced by plot.rhohat) was incorrect
    when rhohat was called with method="piecewise".
    Fixed.

    o markcrosscorr
    Did not recognise the option 'correction="none"'.
    Fixed.

   o roc.ppp
   The default plot of the result of roc.ppp
   did not include the diagonal line 'y=x'.
   Fixed.
   
        CHANGES IN spatstat.core VERSION 2.2-0

OVERVIEW

    o We thank Abdollah Jalilian, Yongtao Guan and Rasmus Waagepetersen
    for contributions.
    
    o summary method for spatial logistic regression models

    o estimation of the spatial covariance function of a pixel image

    o simulation of the product shot noise Cox process.

    o extensions to rhohat
    
NEW FUNCTIONS

    o rPSNCP
    Generate simulated realisations of the product shot noise Cox process.
    Contributed by Abdollah Jalilian, Yongtao Guan and Rasmus Waagepetersen.
    
    o spatcov
    Estimate the spatial covariance function of a pixel image.

    o summary.slrm, print.summary.slrm
    Summary method for spatial logistic regression models

    o coef.summary.slrm
    Print the fitted coefficients, confidence interval and p-values
    for a spatial logistic regression model.

    o pairMean
    Compute the mean of a specified function of interpoint distance
    between random points in a window.

SIGNIFICANT USER-VISIBLE CHANGES

    o rhohat
    New option (smoother='piecewise') computes a piecewise-constant
    estimate of rho(z).
    
    o rhohat
    The result now includes the 'average' intensity rho.

    o distcdf
    Arguments which are NULL will be treated as missing.

    o distcdf
    New argument 'savedenom'.
    

        CHANGES IN spatstat.core VERSION 2.1-2

OVERVIEW

    o Reduced CRAN check time.

        CHANGES IN spatstat.core VERSION 2.1-1

OVERVIEW

    o Minor bug fix

BUG FIXES

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

        CHANGES IN spatstat.core VERSION 2.1-0

OVERVIEW

    o We thank Achmad Choiruddin, Jean-Francois Coeurjolly
    and Rasmus Waagepetersen for contributions.

    o Conditional simulation in kppm
    
    o Information criteria for model selection in kppm

    o Modified handling of covariates in slrm

    o densityfun.ppp handles query points outside original window

    o Improved output in summary.mppm

    o Minor improvements and bug fixes.

NEW FUNCTIONS

    o 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

    o 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'.
    
    o densityfun.ppp
    The resulting function can now handle query points which lie
    outside the window of the original data,
    and has argument 'drop=TRUE' which specifies how to handle them.

    o rpoint
    New argument 'forcewin' forces the code to use the window 'win'
    when 'f' is a pixel image.

    o 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.
    
    o slrm
    Silently ignores any arguments '...' that are not recognised by 'as.mask'

    o summary.mppm
    Improved summary of the dependence of the
    interpoint interaction on the covariates.

    o pairs.im
    New argument 'drop'.
    
BUG FIXES

    o model.matrix.mppm
    If the model was fitted using 'gam', the resulting matrix
    did not have an 'assign' attribute.
    Fixed.
    
    o model.depends
    Crashed for models fitted using 'gam'.
    Fixed.

    o predict.slrm, fitted.slrm
    Crashed if the model was fitted using split pixels (argument 'splitby').
    Fixed.

    o predict.slrm, fitted.slrm
    Crashed in some cases when 'window' was given.
    Fixed.

    o update.slrm
    Failed to find covariates that were provided in 'env'.
    Fixed.

    o cdf.test
    Crashed if the covariate was constant.
    Fixed.

        CHANGES IN spatstat.core VERSION 2.0-0

OVERVIEW

    o We thank Tilman Davies,  Greg McSwiggan and Suman Rakshit
    for contributions.
    
    o Diffusion kernel smoothing.
    
    o More support for spatial logistic regression models.

NEW FUNCTIONS

    o densityHeat, densityHeat.ppp
    Given a point pattern, compute the diffusion kernel estimate
    of point process intensity. This is an alternative to density.ppp.
    
SIGNIFICANT USER-VISIBLE CHANGES

    o slrm
    'step' can now be applied to models fitted using 'slrm'.


        CHANGES IN spatstat.core VERSION 1.65-11

OVERVIEW

    o Internal tweaks.
    
        CHANGES IN spatstat.core VERSION 1.65-10

OVERVIEW

    o Minor corrections to documentation.

        CHANGES IN spatstat.core VERSION 1.65-9

OVERVIEW

    o We thank Ian Buller for a suggestion.

    o weights permitted in density calculation for line segments.

SIGNIFICANT USER-VISIBLE CHANGES

    o density.psp
    New argument 'weights'.

        CHANGES IN spatstat.core VERSION 1.65-8

OVERVIEW

    o Minor changes to appease the compiler.

        CHANGES IN spatstat.core VERSION 1.65-7

OVERVIEW

    o We thank Michael Chirico for a contribution.

    o Minor changes to appease the compiler.
    
        CHANGES IN spatstat.core VERSION 1.65-6

OVERVIEW

    o We thank Tilman Davies and Pavel Fibich for contributions.

    o Important bug fix in simulation of log-Gaussian Cox processes.

    o Increased speed for large datasets.

    o variance calculations handle larger datasets.
    
SIGNIFICANT USER-VISIBLE CHANGES

    o vcov.ppm, summary.ppm
    Variance calculations now handle larger datasets
    (using sparse arrays).
    
    o rSSI
    Accelerated.
    
    o overall speed
    Changes have been made to the internal code of spatstat 
    which should accelerate computations involving large datasets.

    o localpcf, localpcfinhom
    New argument 'rvalue'.

BUG FIXES

    o rLGCP, 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.
    
    o Vmark
    Crashed if normalise=TRUE when there was only one column of marks.
    (Spotted by Pavel Fibich.)
    Fixed.
    
    o nnclean
    Crashed if k >= npoints(X).
    Fixed.

    o print.ppm
    Crashed sometimes when applied to the result of subfits().
    Fixed.
    
    CHANGES IN spatstat.core VERSION 1.65-5

OVERVIEW

    o Minor changes required by CRAN.
    

        CHANGES IN spatstat.core VERSION 1.65-1

OVERVIEW

    o Added NEWS file.


        CHANGES IN spatstat.core VERSION 1.65-0

OVERVIEW

    o Package initialised at version 1.65-0

SIGNIFICANT USER-VISIBLE CHANGES

    o 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")

    o 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.



