Package: spatstat
Version: 1.17-1
Date: 04 november 2009
Title: Spatial Point Pattern analysis, model-fitting, simulation, tests
Author: Adrian Baddeley <adrian@maths.uwa.edu.au> and Rolf Turner
        <r.turner@auckland.ac.nz>, with substantial contributions of
        code by Marie-Colette van Lieshout, Rasmus Waagepetersen,
        Kasper Klitgaard Berthelsen and Dominic Schuhmacher. Additional
        contributions by Ang Qi Wei, C. Beale, R. Bernhardt, B.
        Biggerstaff, R. Bivand, F. Bonneu, J. Burgos, J.B. Chen, Y.C.
        Chin, B. Christensen, M. de la Cruz, P.J. Diggle, S. Eglen, A.
        Gault, M. Genton, P. Grabarnik, C. Graf, J. Franklin, U. Hahn,
        M. Hering, M.B. Hansen, M. Hazelton, J. Heikkinen, K. Hornik,
        R. Ihaka, R. John-Chandran, D. Johnson, J. Laake, R. Mark, J.
        Mateu, P. McCullagh, S. Meyer, X.C. Mi, J. Moller, L.S.
        Nielsen, F. Nunes, E. Parilov, J. Picka, M. Reiter, B.D.
        Ripley, B. Rowlingson, E. Rubak, J. Rudge, A. Sarkka, K.
        Schladitz, B.T. Scott, I.-M. Sintorn, M. Spiess, M. Stevenson,
        P. Surovy, B. Turlach, A. van Burgel, T. Verbeke, A. Villers,
        H. Wang, H. Wendrock and S. Wong.
Maintainer: Adrian Baddeley <adrian@maths.uwa.edu.au>
Depends: R (>= 2.10.0), stats, graphics, utils, mgcv, deldir (>= 0.0-7)
Suggests: gpclib, sm, maptools, rpanel, tkrplot, scatterplot3d
Description: A package for analysing spatial data, mainly Spatial Point
        Patterns, including multitype/marked points and spatial
        covariates, in any two-dimensional spatial region. Contains
        functions for plotting spatial data, exploratory data analysis,
        model-fitting, simulation, spatial sampling, model diagnostics,
        and formal inference. Data types include point patterns, line
        segment patterns, spatial windows, and pixel images. Point
        process models can be fitted to point pattern data. Cluster
        type models are fitted by the method of minimum contrast. Very
        general Gibbs point process models can be fitted to point
        pattern data using a function ppm similar to lm or glm. Models
        may include dependence on covariates, interpoint interaction
        and dependence on marks. Fitted models can be simulated
        automatically. Also provides facilities for formal inference
        (such as chi-squared tests) and model diagnostics (including
        simulation envelopes, residuals, residual plots and Q-Q plots).
License: GPL (>= 2)
URL: http://www.spatstat.org
Packaged: 2009-11-06 03:02:06 UTC; adrian
Repository: CRAN
Date/Publication: 2009-11-06 10:18:11