whittermore.boot
(Package: DCluster) :
Generate Bootstrap Replicates of Whittermore's Statistic
Generate bootstrap replicates of Whittermore's statistic by means of function boot from boot library. Notice that these functions should not be used separately but as argument statistic when calling function boot.
● Data Source:
CranContrib
● Keywords: spatial
● Alias: whittermore.boot, whittermore.pboot
●
4 images
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Compute Whittermore's statistic. See whittermore manual page for more details.
● Data Source:
CranContrib
● Keywords: spatial
● Alias: whittermore.stat, whittermore.test
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0 images
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Tests for Overdispertion
(Package: DCluster) :
Likelihood Ratio Test and Dean's Tests for Overdispertion
When working with count data, the assumption of a Poisson model is common. However, sometimes the variance of the data is significantly higher that their mean which means that the assumption of that data have been drawn from a Poisson distribution is wrong.
● Data Source:
CranContrib
● Keywords: htest
● Alias: DeanB, DeanB2, test.nb.pois
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0 images
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moranI.boot
(Package: DCluster) :
Generate Bootstrap Replicates of Moran's I Autocorrelation Statistic
Generate bootstrap replicates of Moran's I autocorrelation statistic, by means of function boot form boot library. Notice that these functions should not be used separately but as argument statistic when calling function boot.
● Data Source:
CranContrib
● Keywords: spatial
● Alias: moranI.boot, moranI.pboot
●
4 images
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achisq
(Package: DCluster) :
Another Implementation of Pearson's Chi-square Statistic
Another implementation of Pearson's Chi-square has been written to fit the needs in package DCLuster.
● Data Source:
CranContrib
● Keywords: htest
● Alias: achisq
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0 images
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rmultin
(Package: DCluster) :
Generate Random Observations from a Multinomial Distribution
This function generates a random observation from a multinomial distribution.
● Data Source:
CranContrib
● Keywords: distribution
● Alias: rmultin
●
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opgam
(Package: DCluster) :
Openshaw's GAM
Scan an area with Openshaw's Geographical Analysis Machine to look for clusters.
● Data Source:
CranContrib
● Keywords: spatial
● Alias: opgam, opgam.intern
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1 images
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gearyc.boot
(Package: DCluster) :
Generate Bootstrap Replicates of Geary's C Autocorrelation Statistic
Generate bootstrap replicates of Geary's C autocorrelation statistic, by means of function boot form boot library. Notice that these functions should not be used separately but as argument statistic when calling function boot.
● Data Source:
CranContrib
● Keywords: spatial
● Alias: gearyc.boot, gearyc.pboot
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4 images
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besagnewell.stat
(Package: DCluster) :
Besag and Newell's Statistic for Spatial Clustering
besagnewell.stat computes the statistic around a single location. Data passed must be sorted according to distance to central region, which is supposed to be the first row in the dataframe. Notice that the size of the cluster is k+1.
● Data Source:
CranContrib
● Keywords: spatial
● Alias: besagnewell.stat
●
0 images
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stone.boot
(Package: DCluster) :
Generate Boostrap Replicates of Stone's Statistic
Generate bootstrap replicates of Stone's statictic, by means of function boot from boot package. Notice that these functions should not be used separately but as argument statistic when calling function boot.
● Data Source:
CranContrib
● Keywords: spatial
● Alias: stone.boot, stone.pboot
●
4 images
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providing 
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