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DCluster (version 0.2-2)

Functions for the detection of spatial clusters of diseases

Description

A set of functions for the detection of spatial clusters of disease using count data. Bootstrap is used to estimate sampling distributions of statistics.

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Version

Install

install.packages('DCluster')

Monthly Downloads

516

Version

0.2-2

License

GPL (>= 2)

Maintainer

Virgilio Gf3mez-Rubio

Last Published

February 5th, 2024

Functions in DCluster (0.2-2)

achisq.stat

Another implementation of Pearson's Chi-square statistic
gearyc.boot

Generate bootstrap replicates of Moran's I autocorrelation statistic
empbaysmooth

Empirical Bayes Smoothing
pottwhitt

Potthoff-Whittinghill's statistic for overdispersion
besagnewell.stat

Besag and Newell's statistic for spatial clustering
gearyc

Moran's I autocorrelation statistic
achisq.boot

Bootstrap replicates of Pearson's Chi-square statistic
stone.stat

Compute Stone's statistic
tango.stat

Compute Tango's statistic for general clustering
DCluster-internal

Internal functions in the DCluster package.
kullnagar.stat

Kulldorff and Nagarwalla's statistic for spatial clustering.
kullnagar

Kulldorff and Nagarwalla's statistic for spatial clustering.
DCluster

A package for the detection of spatial clusters of diseases for count data
kullnagar.boot

Generate bootstrap replicates of Kulldorff and Nagarwalla's statistic
iscluster

Local clustering test function
calculate.mle

Calculate parameters involved in smapling procedures
besagnewell

Besag and Newell's statistic for spatial clustering
moranI

Compute Moran's I autocorrelation statistic
gearyc.stat

Compute Moran's I autocorrelation statistic
stone

Stone's Test
pottwhitt.stat

Compute Potthoff-Whittinghill's statistic
achisq

Another implementation of Pearson's Chi-square statistic
tango.boot

Generate bootstrap replicated of Tango's statistic
pottwhitt.boot

Bootstrap replicates of Potthoff-Whittinghill's statistic
moranI.boot

Generate bootstrap replicates of Moran's I autocorrelation statistic
lognormalEB

Empirical Bayes Smoothing using a log-normal model
whittermore.stat

Compute Whittermore's statistic
Tests for Overdispertion

Likelihood ratio test and Dean's tests for Overdispertion
bn.iscluster

Clustering function for Besag and Newell's method
besagnewell.boot

Generate boostrap replicates of Besag and Newell's statistic
observed.sim

Randomly generate observed cases from different statistical distributions
whittermore.boot

Generate bootstrap replicates of Whittermore's statistic
whittermore

Whittermore's statistic
stone.boot

Generate boostrap replicates of Stone's statistic
kn.iscluster

Clustering function for Kulldorff and Nagarwalla's statistic
rmultin

Generate random observations from a multinomial distribution
tango

Tango's statistic for general clustering
opgam

Openshaw's GAM
get.knclusters

Get areas in a cluster detected with Kulldorff's statistic
moranI.stat

Compute Moran's I autocorrelation statistic