Skip to content
Sections
>> Trisquel >> Пакеты >> aramo >> gnu-r >> r-cran-spatstat.core
[  aramo  ]
[ Источник: r-cran-spatstat.core  ]

Пакет: r-cran-spatstat.core (2.3-2-1)

core functionality of the 'spatstat' family of GNU R packages

Functionality for data analysis and modelling of spatial data, mainly spatial point patterns, in the 'spatstat' family of packages. (Excludes analysis of spatial data on a linear network, which is covered by the separate package 'spatstat.linnet'.) Exploratory methods include quadrat counts, K-functions and their simulation envelopes, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross- validated bandwidth selection, mark correlation functions, segregation indices, mark dependence diagnostics, and kernel estimates of covariate effects. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov- Smirnov, Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two- stage Monte Carlo) and tests for covariate effects (Cox-Berman-Waller- Lawson, Kolmogorov-Smirnov, ANOVA) 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 (likelihood ratio test, analysis of deviance, Monte Carlo tests) along with basic tools for model selection (stepwise(), AIC()) and variable selection (sdr). Tools for validating the fitted model include simulation envelopes, residuals, residual plots and Q-Q plots, leverage and influence diagnostics, partial residuals, and added variable plots.

Другие пакеты, относящиеся к r-cran-spatstat.core

  • зависимости
  • рекомендации
  • предложения
  • dep: libc6 (>= 2.29)
    GNU C Library: Shared libraries
    также виртуальный пакет, предоставляемый libc6-udeb
  • dep: libstdc++6 (>= 5)
    GNU Standard C++ Library v3
  • dep: r-api-4.0
    виртуальный пакет, предоставляемый r-base-core
  • dep: r-base-core (>= 4.1.2-1ubuntu1)
    GNU R core of statistical computation and graphics system
  • dep: r-cran-abind
    GNU R abind multi-dimensional array combination function
  • dep: r-cran-goftest (>= 1.2-2)
    GNU R Classical Goodness-of-Fit Tests for Univariate Distributions
  • dep: r-cran-matrix
    GNU R package of classes for dense and sparse matrices
  • dep: r-cran-mgcv
    GNU R package for multiple parameter smoothing estimation
  • dep: r-cran-nlme
    GNU R package for (non-)linear mixed effects models
  • dep: r-cran-rpart
    GNU R package for recursive partitioning and regression trees
  • dep: r-cran-spatstat.data (>= 2.1-0)
    datasets for the package r-cran-spatstat
  • dep: r-cran-spatstat.geom (>= 2.3-0)
    GNU R geometrical functionality of the 'spatstat' package
  • dep: r-cran-spatstat.sparse (>= 2.0-0)
    GNU R sparse three-dimensional arrays and linear algebra utilities
  • dep: r-cran-spatstat.utils (>= 2.2-0)
    GNU R utility functions for r-cran-spatstat
  • dep: r-cran-tensor
    GNU R Tensor product of arrays
  • sug: r-cran-gsl
    GNU R wrapper for the GNU Scientific Library
  • sug: r-cran-locfit
    GNU R local regression, likelihood and density estimation
  • sug: r-cran-maptools (>= 0.9-9)
    GNU R Tools for reading and handling spatial objects
  • sug: r-cran-nleqslv
    GNU R package for solving systems of nonlinear equations
  • sug: r-cran-randomfields (>= 3.1.24.1)
    GNU R simulation and analysis of random fields
  • sug: r-cran-randomfieldsutils (>= 0.3.3.1)
    utilities for the simulation and analysis of random fields
  • sug: r-cran-sm
    GNU R package for kernel smoothing methods
  • sug: r-cran-spatial
    GNU R package for spatial statistics
  • sug: r-cran-spatstat (>= 2.0-0)
    GNU R Spatial Point Pattern analysis, model-fitting, simulation, tests
  • sug: r-cran-spatstat.linnet (>= 2.0-0)
    linear networks functionality of the 'spatstat' family of GNU R

Загрузка r-cran-spatstat.core

Загрузить для всех доступных архитектур
Архитектура Размер пакета В установленном виде Файлы
amd64 6 560,0 Кб7366 Кб [список файлов]