nnspat package - RDocumentation

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This is an R package that contains the functions for generating patterns of segregation, association, Uniform data, and various non-random labeling patterns for disease clustering in two dimensional cases, and for testing the spatial patterns (of segregation, spatial symmetry, association, disease clustering, species correspondence and reflexivity) based on NN relations, especially using contingency tables such as nearest neighbor contingency tables, NN symmetry contingency tables, species correspondence contingency tables and reflexivity contingency tables for two- and higher-dimensional data, for visualization for the two dimensional data. The tests are usually (asymptotic) normal z-tests and chi-square tests.

Install from GitHub : devtools::install_github("elvanceyhan/nnspat")

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Version

Install

install.packages('nnspat')

Monthly Downloads

153

Version

0.1.2

License

GPL-2

Maintainer

Elvan Ceyhan

Last Published

December 19th, 2023

Functions in nnspat (0.1.2)

\(N_{tkl}\) Value

\(T\) value in NN structure

Pielou's Second Type of NN Symmetry Test with Chi-square Approximation

Skewness of Cuzick and Edwards \(T_k\) Test statistic

Cuzick & Edwards Tcomb Test Statistic

\(Q\)-symmetry Contingency Table (QCT)

Vector of Shared NNs and Number of Reflexive NNs

Finding the index of the NN of a given point among a subset of points

\(N_t\) Value (found with the definition formula)

Number of Shared and Reflexive NNs

Asymptotic Covariance between \(T_k\) and \(T_l\) Values

The incidence matrix W for the NN digraph

Chi-square Approximation to Cuzick and Edwards \(T_k\) Test statistic

NN Symmetry Test with Normal Approximation

Overall NN Symmetry Test with Chi-square Approximation

\(Z\)-test for Cuzick and Edwards \(T_{run}\) statistic

NN Symmetry Test with Normal Approximation for Two Classes

Closeness or Proximity Matrix for Tango's Spatial Clustering Tests

\(Z\)-test for Cuzick and Edwards \(T_{comb}\) statistic

\(Z\)-test for Cuzick and Edwards \(T_k\) statistic

Cuzick and Edwards \(T_{run}\) Test statistic

Covariance Matrix of the Entries of the Type I-IV TCTs

Asymptotic Variance of Cuzick and Edwards \(T_k\) Test statistic

pdf of the Bivariate Normal Distribution

Cuzick and Edwards \(T_k^{inv}\) Test statistic

Entries for the Types I-IV cell-specific tests

Covariance Matrix of the Differences of the Off-Diagonal Cell Counts in an NNCT

Covariance Matrix of Segregation Coefficients in a Multi-class Case

Covariance Matrix of the Cell Counts in an NNCT

Cuzick and Edwards \(T_k\) Test statistic

.onLoad getOption package settings

Exact version of Pearson's chi-square test on NNCTs

Converts a lower triangular distance matrix to a full distance matrix

Conversion of the Covariance Matrix of the Row-wise Vectorized Cell Counts to Column-wise Vectorized Cell Counts in an NNCT

The Euclidean distance between two vectors, matrices, or data frames

Finite Sample Covariance between \(T_k\) and \(T_l\) Values

\(p\)-value correction to the one-sided version of exact NNCT test

Interpoint Distance Matrix for Standardized Data

Covariance matrix for \(T_k\) values in Tcomb

.onAttach start message

funs.class.spec

Class-specific Chi-square Tests based on NNCTs

funs.overall.nnct

Dixon's Overall Test of Segregation for NNCT

\(p\)-value correction to the two-sided version of exact NNCT test

Functions for the \(k^{th}\) and k NN distances

funs.kNNdist2cl

Functions for the \(k^{th}\) and k NN distances

Functions for Covariances of the Entries of the Types I, III and IV TCTs

funs.cell.spec.ss

Pielou's Cell-specific Segregation Test with Normal Approximation (for Sparse Sampling)

funs.base.class.spec

Base Class-specific Chi-square Tests based on NNCTs

Auxiliary Functions for Computing Covariances Between Cell Counts in the TCT

Covariance Matrix of the Self Entries in a Species Correspondence Contingency Table (SCCT)

Variances of the Self Entries in a Species Correspondence Contingency Table (SCCT)

Species Correspondence Contingency Table (SCCT)

Correction Matrices for the Covariance Matrix of NNCT entries

funs.overall.seg

Overall Segregation Tests for NNCTs

Expected Value for Cuzick and Edwards \(T_k\) Test statistic

Aij matrices for computation of Moments of Cuzick and Edwards \(T_k\) Test statistic

Pielou's Segregation Coefficients for NNCTs

funs.overall.tct

Types I-IV Overall Tests of Segregation for NNCT

The functions for probability of selecting a number of points from respective classes

Functions for Variances of Cell Counts in the Types I, III and IV TCTs

Functions for row and column sums of a matrix

Functions for one versus rest type labeling

Pielou's Overall Test of Segregation for NNCT (for Sparse Sampling)

Expected Value for Cuzick and Edwards \(T_{run}\) Test statistic

funsNNclass.spec

NN Class-specific Chi-square Tests based on NNCTs

Variance of Cuzick and Edwards \(T_{run}\) Test statistic

Functions for the number of shared NNs, shared NN vector, and the number of reflexive NNs

\(W_k\) values for Tango's \(T\) test statistic

Correction Matrices for the NNCT entries

Variance of Cuzick and Edwards \(T_k\) Test statistic

Reflexivity Test with Chi-square Approximation

Types I-IV Cell-specific Z Tests of Segregation based on NNCTs

funsZcell.nnct.pval

\(p\)-values for Cell-specific Z Test Statistics for NNCT

funsXsq.nnsym.ss

Pielou's First Type of NN Symmetry Test with Chi-square Approximation for multiple classes (for Sparse Sampling)

Cell-specific Z Tests of Segregation for NNCTs

Dixon's Cell-specific Z Tests of Segregation for NNCT

funsXsq.nnsym.dx

Dixon's NN Symmetry Test with Chi-square Approximation for multiple classes

Z-Test for Cuzick and Edwards \(T_k^{inv}\) statistic

funsXsq.spec.cor

Overall Species Correspondence Test with Chi-square Approximation

funsXsq.seg.coeff

Chi-square Test for Segregation Coefficients

Z Tests for NN Reflexivity

funsZdir.nnct.ss

Directional Segregation Test for Two Classes with Normal Approximation (for Sparse Sampling)

Directional Segregation Test for Two Classes with Normal Approximation

funsZmixed.nonref

Mixed-Non-Reflexivity Test with Normal Approximation

Pielou's Pairwise NN Symmetry Test with Normal Approximation (for Sparse Sampling)

Dixon's Pairwise NN Symmetry Test with Normal Approximation

funsZnnself.sum

Cumulative Species Correspondence Test with Normal Approximation

funsZnnsym2cl.dx

Dixon's NN Symmetry Test with Normal Approximation for Two Classes

funsZnnsym2cl.ss

Pielou's First Type of NN Symmetry Test with Normal Approximation for Two Classes (for Sparse Sampling)

Self-Reflexivity Tests with Normal Approximation

Square root of a matrix

Z Tests for Segregation Indices

Index Matrix for Computing the Covariance of Dixon's Overall NN Symmetry Test

Finding the indices of the k NNs of a given point

Conversion of a Matrix to a Vector

Z Tests for Segregation Coefficients

Self-Reflexivity Test with Normal Approximation

Euclidean Interpoint Distance Matrix

Interpoint Distance Matrix

Index Matrix for Computing the Covariance of Segregation Coefficients

Bootstrap Nearest Neighbor Contingency Table (NNCT)

Keeping the pair of the specified labels in the data

Nearest Neighbor Contingency Table (NNCT)

plot.SpatPatterns

Plot a SpatPatterns object

Smallest and Largest Distances in a Distance Matrix

Plot a Clusters object

nnspat: A package for NN Methods and Their Use in Testing Spatial Patterns

Probability of k items selected from the class with size \(n_1\)

Nearest Neighbor Contingency Table (NNCT) with (only) base points restricted to a subsample

print.Chisqtest

Print a summary of a Chisqtest object

print.summary.SpatPatterns

Print a summary of a SpatPatterns object

Generation of Points Associated with a Given Set of Points

print.summary.Clusters

Print a summary of a Clusters object

Print a summary of a refhtest object

print.classhtest

Print a summary of a classhtest object

print.cellhtest

Print a summary of a cellhtest object

print.SpatPatterns

Print a SpatPatterns object

Generation of Points Associated in the Type C Sense with a Given Set of Points

Print a Clusters object

Probability of the current nearest neighbor contingency table

Generation of Points with Clusters along the Horizontal Axis

Generation of Points Associated in the Type G Sense with a Given Set of Points

Generation of Points Associated in the Type I Sense with a Given Set of Points

Type III Non-Random Labeling of a Given Set of Points

Generation of Points Associated in the Type U Sense with a Given Set of Points

Reflexivity Contingency Table (RCT)

Generation of Points with Clusters along the First Diagonal

Non-Random Labeling of a Given Set of Points

Type II Non-Random Labeling of a Given Set of Points

Type I Non-Random Labeling of a Given Set of Points

Generation of Points with Rotational Clusters

Generation of Points under Segregation of Two Classes

The Shared NN Vectors for Multiple Classes

Dixon's Segregation Indices for NNCTs

Tree Species in a Swamp Forest

summary.Clusters

Return a summary of a Clusters object

summary.SpatPatterns

Return a summary of a SpatPatterns object

Type IV Non-Random Labeling of a Given Set of Points

Generation of Points from Self Correspondence Pattern

Generation of Uniform Points in a Circle

Simulated Variance of Cuzick and Edwards \(T_k^{inv}\) Test statistic

Variances of Cell Counts in an NNCT

\(T\) Contingency Table (TCT)

Variances of Segregation Coefficients in a Multi-class Case

Variances of Differences of Off-Diagonal Entries in an NNCT

Tocher's randomized correction to the exact \(p\)-value

Variance of Pielou's Segregation Coefficient for 2 Classes

Variances of Entries in a TCT

Distances between subjects and their NNs

Expected Values of the Type I cell-specific tests

Expected Values of the Self Entries in a Species Correspondence Contingency Table (SCCT)

Finding the index of the NN of a given point

Expected Values of the Cell Counts in NNCT

Expected Values of the Types I-IV cell-specific tests

Expected Values of the Cell Counts in RCT

Expected Value of Cuzick and Edwards \(T_k^{inv}\) Test statistic

Distances between subjects from class \(i\) and their NNs from class \(j\)

Expected Value for Cuzick & Edwards \(T_{comb}\) Test Statistic