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| achisq | Another implementation of Pearson's Chi-square statistic |
| achisq.boot | Bootstrap replicates of Pearson's Chi-square statistic |
| achisq.pboot | Bootstrap replicates of Pearson's Chi-square statistic |
| achisq.stat | Another implementation of Pearson's Chi-square statistic |
| achisq.test | Another implementation of Pearson's Chi-square statistic |
| besagnewell | Besag and Newell's statistic for spatial clustering |
| besagnewell.boot | Generate boostrap replicates of Besag and Newell's statistic |
| besagnewell.pboot | Generate boostrap replicates of Besag and Newell's statistic |
| besagnewell.stat | Besag and Newell's statistic for spatial clustering |
| bn.iscluster | Clustering function for Besag and Newell's method |
| calculate.mle | Calculate parameters involved in smapling procedures |
| DCluster | A package for the detection of spatial clusters of diseases for count data |
| DeanB | Likelihood ratio test and Dean's tests for Overdispertion |
| DeanB2 | Likelihood ratio test and Dean's tests for Overdispertion |
| empbaysmooth | Empirical Bayes Smoothing |
| gearyc | Moran's I autocorrelation statistic |
| gearyc.boot | Generate bootstrap replicates of Moran's I autocorrelation statistic |
| gearyc.pboot | Generate bootstrap replicates of Moran's I autocorrelation statistic |
| gearyc.stat | Compute Moran's I autocorrelation statistic |
| gearyc.test | Compute Moran's I autocorrelation statistic |
| get.knclusters | Get areas in a cluster detected with Kulldorff's statistic |
| kn.iscluster | Clustering function for Kulldorff and Nagarwalla's statistic |
| kullnagar | Kulldorff and Nagarwalla's statistic for spatial clustering. |
| kullnagar.boot | Generate bootstrap replicates of Kulldorff and Nagarwalla's statistic |
| kullnagar.pboot | Generate bootstrap replicates of Kulldorff and Nagarwalla's statistic |
| kullnagar.stat | Kulldorff and Nagarwalla's statistic for spatial clustering. |
| kullnagar.stat.bern | Kulldorff and Nagarwalla's statistic for spatial clustering. |
| kullnagar.stat.poisson | Kulldorff and Nagarwalla's statistic for spatial clustering. |
| lognormalEB | Empirical Bayes Smoothing using a log-normal model |
| moranI | Moran's I autocorrelation statistic |
| moranI.boot | Generate bootstrap replicates of Moran's I autocorrelation statistic |
| moranI.pboot | Generate bootstrap replicates of Moran's I autocorrelation statistic |
| moranI.stat | Compute Moran's I autocorrelation statistic |
| moranI.test | Compute Moran's I autocorrelation statistic |
| multinom.sim | Randomly generate observed cases from different statistical distributions |
| negbin.sim | Randomly generate observed cases from different statistical distributions |
| opgam | Openshaw's GAM |
| opgam.intern | Openshaw's GAM |
| opgam.iscluster.default | Local clustering test function |
| opgam.iscluster.negbin | Local clustering test function |
| plot.dcluster | Class for results from a test for the detection of disease clusters |
| poisson.sim | Randomly generate observed cases from different statistical distributions |
| pottwhitt | Potthoff-Whittinghill's statistic for overdispersion |
| pottwhitt.boot | Bootstrap replicates of Potthoff-Whittinghill's statistic |
| pottwhitt.pboot | Bootstrap replicates of Potthoff-Whittinghill's statistic |
| pottwhitt.stat | Compute Potthoff-Whittinghill's statistic |
| pottwhitt.test | Compute Potthoff-Whittinghill's statistic |
| print.dcluster | Class for results from a test for the detection of disease clusters |
| rmultin | Generate random observations from a multinomial distribution |
| stone | Stone's Test |
| stone.boot | Generate boostrap replicates of Stone's statistic |
| stone.pboot | Generate boostrap replicates of Stone's statistic |
| stone.stat | Compute Stone's statistic |
| stone.test | Compute Stone's statistic |
| summary.dcluster | Class for results from a test for the detection of disease clusters |
| tango | Tango's statistic for general clustering |
| tango.boot | Generate bootstrap replicated of Tango's statistic |
| tango.pboot | Generate bootstrap replicated of Tango's statistic |
| tango.stat | Compute Tango's statistic for general clustering |
| tango.test | Compute Tango's statistic for general clustering |
| test.nb.pois | Likelihood ratio test and Dean's tests for Overdispertion |
| whittermore | Whittermore's statistic |
| whittermore.boot | Generate bootstrap replicates of Whittermore's statistic |
| whittermore.pboot | Generate bootstrap replicates of Whittermore's statistic |
| whittermore.stat | Compute Whittermore's statistic |
| whittermore.test | Compute Whittermore's statistic |