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It contains all the main user-level functions that perform\n**parametric statistical modelling** of spatial data,\nwith the exception of data on linear networks.\n\nMost of the functionality is for spatial point patterns in two dimensions.\nThere is a very modest amount of functionality for 3D and higher dimensional patterns\nand space-time patterns.\n\n### Overview \n\n`spatstat.model` supports\n\n- parametric modelling (fitting models to point pattern data, model selection, model prediction)\n- formal inference (hypothesis tests, confidence intervals)\n- informal validation (model diagnostics)\n\n### Detailed contents\n\nFor a full list of functions, see the help file for `spatstat.model-package`.\n\n#### Parametric modelling \n- fitting Poisson point process models to point pattern data (`ppm`)\n- fitting spatial logistic regression models to point pattern data (`slrm`)\n- fitting Cox point process models to point pattern data (`kppm`)\n- fitting Neyman-Scott cluster process models to point pattern data (`kppm`)\n- fitting Gibbs point process models to point pattern data (`ppm`)\n- fitting determinantal point process models to point pattern data (`dppm`)\n- fitting recursively partitioned models to point patterns (`rppm`)\n- class support for fitted models (`update`, `print`, `summary`, `predict`, `plot`, `simulate`, `coef`, `confint`, `vcov`, `anova`, `residuals`, `fitted`, `deviance`, `AIC`, `logLik`, `terms`, `formula`, `model.matrix`)\n- minimum contrast estimation (generic algorithm)\n- simulation of fitted point process models\n\n#### Formal inference\n\n- hypothesis tests (quadrat test, Clark-Evans test, Berman test, Diggle-Cressie-Loosmore-Ford test, scan test, studentised permutation test, segregation test, ANOVA tests of fitted models, adjusted composite\nlikelihood ratio test, envelope tests, Dao-Genton test, balanced independent two-stage test)\n- confidence intervals for parameters of a model\n- prediction intervals for point counts\n\n#### Informal validation\n\n- residuals\n- leverage\n- influence\n- partial residual plot\n- added variable plot\n- diagnostic plots\n- pseudoscore residual plots\n- model compensators of summary functions\n- Q-Q plots\n\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fspatstat%2Fspatstat.model","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fspatstat%2Fspatstat.model","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fspatstat%2Fspatstat.model/lists"}