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nnspat  

Nearest Neighbor Methods for Spatial Patterns
View on CRAN: Click here


Download and install nnspat package within the R console
Install from CRAN:
install.packages("nnspat")

Install from Github:
library("remotes")
install_github("cran/nnspat")

Install by package version:
library("remotes")
install_version("nnspat", "0.1.2")



Attach the package and use:
library("nnspat")
Maintained by
Elvan Ceyhan
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-05-10
Latest Update: 2023-12-19
Description:
Contains the functions for testing the spatial patterns (of segregation, spatial symmetry, association, disease clustering, species correspondence, and reflexivity) based on nearest neighbor relations, especially using contingency tables such as nearest neighbor contingency tables (Ceyhan (2010) and Ceyhan (2017) and references therein), nearest neighbor symmetry contingency tables (Ceyhan (2014) ), species correspondence contingency tables and reflexivity contingency tables (Ceyhan (2018) for two (or higher) dimensional data. The package also contains functions for generating patterns of segregation, association, uniformity in a multi-class setting (Ceyhan (2014) ), and various non-random labeling patterns for disease clustering in two dimensional cases (Ceyhan (2014) ), and for visualization of all these patterns for the two dimensional data. The tests are usually (asymptotic) normal z-tests or chi-square tests.
How to cite:
Elvan Ceyhan (2021). nnspat: Nearest Neighbor Methods for Spatial Patterns. R package version 0.1.2, https://cran.r-project.org/web/packages/nnspat
Previous versions and publish date:
0.1.0 (2021-05-10 09:30), 0.1.1 (2022-08-30 09:00)
Other packages that cited nnspat R package
View nnspat citation profile
Other R packages that nnspat depends, imports, suggests or enhances
Functions, R codes and Examples using the nnspat R package
Some associated functions: EV.Nii . EV.Tcomb . EV.Tkinv . EV.nnct . EV.rct . EV.tct . EV.tctI . NN . NNdist . NNdist2cl . NNsub . Ninv . Nt.def . Ntkl . QRval . Qsym.ct . Qsym.test . SkewTk . Tcomb . Tval . Wmat . Xsq.ceTk . Xsq.nnsym . ZTcomb . ZTrun . ZceTk . Znnsym . Znnsym2cl . aij.theta . asycovTkTl . asyvarTk . bvnorm.pdf . ceTk . ceTkinv . ceTrun . cellsTij . cov.nnct . cov.nnsym . cov.seg.coeff . cov.tct . covNrow2col . covTcomb . covTkTl . dist.std.data . dist2full . dot-onAttach . dot-onLoad . euc.dist . exact.nnct . exact.pval1s . exact.pval2s . funs.auxcovtct . funs.base.class.spec . funs.cell.spec.ss . funs.class.spec . funs.covNii . funs.covtct . funs.kNNdist . funs.kNNdist2cl . funs.overall.nnct . funs.overall.seg . funs.overall.tct . funs.pijPij . funs.scct . funs.seg.coeff . funs.varNii . funs.vartct . funsAijmat . funsC_MI_II . funsExpTk . funsExpTrun . funsNNclass.spec . funsN_I_II . funsOnevsRest . funsPseg.ss . funsQandR . funsRowColSums . funsVarTk . funsVarTrun . funsW345values . funsXsq.nnref . funsXsq.nnsym.dx . funsXsq.nnsym.ss . funsXsq.seg.coeff . funsXsq.spec.cor . funsZTkinv . funsZcell.nnct . funsZcell.nnct.pval . funsZcell.spec . funsZcell.tct . funsZdir.nnct . funsZdir.nnct.ss . funsZmixed.nonref . funsZnnref . funsZnnself . funsZnnself.sum . funsZnnsym.dx . funsZnnsym.ss . funsZnnsym2cl.dx . funsZnnsym2cl.ss . funsZseg.coeff . funsZsegind . funsZself.ref . ind.nnsym . ind.seg.coeff . ipd.mat.euc . ipd.mat . kNN . mat2vec . matrix.sqrt . nnct.boot.dis . nnct . nnct.sub . nnspat-package . pairwise.lab . pick.min.max . pk . plot.Clusters . plot.SpatPatterns . print.Chisqtest . print.Clusters . print.SpatPatterns . print.cellhtest . print.classhtest . print.refhtest . print.summary.Clusters . print.summary.SpatPatterns . prob.nnct . rassoc . rassocC . rassocG . rassocI . rassocU . rct . rdiag.clust . rhor.clust . rnonRL . rnonRLI . rnonRLII . rnonRLIII . rnonRLIV . rrot.clust . rseg . rself.ref . runif.circ . seg.ind . sharedNNmc . summary.Clusters . summary.SpatPatterns . swamptrees . tct . tocher.cor . var.nnct . var.nnsym . var.seg.coeff . var.tct . varPseg.coeff . varTkinv.sim . 
Some associated R codes: ClassFunctions.R . NNCTFunctions.R . StartupFunctions.R . data.R . nnspat.R .  Full nnspat package functions and examples
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