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DClusterm (version 1.0-1)

Model-Based Detection of Disease Clusters

Description

Model-based methods for the detection of disease clusters using GLMs, GLMMs and zero-inflated models. These methods are described in 'V. Gmez-Rubio et al.' (2019) and 'V. Gmez-Rubio et al.' (2018) .

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Version

Install

install.packages('DClusterm')

Monthly Downloads

261

Version

1.0-1

License

GPL-3

Maintainer

Virgilio Gf3mez-Rubio

Last Published

February 25th, 2020

Functions in DClusterm (1.0-1)

get.stclusters

Gets areas in a spatio-temporal cluster
get.allknclusters

Extract indices of the areas in the clusters detected
glmAndZIP.iscluster

Obtains the cluster with the maximum log-likelihood ratio or minimum DIC of all the clusters with the same center and start and end dates.
knbinary

Constructs data frame with clusters in binary format.
SetVbleCluster

Constructs a variable that indicates the locations and times that pertain to a cluster.
slimknclusters

Remove overlapping clusters
mergeknclusters

Merges clusters so that they are identifed as levels of a factor.
brainNM

Brain cancer in New Mexico, USA, 1973-1991.
CalcStatsAllClusters

Obtains the clusters with the maximum log-likelihood ratio or minimum DIC for each center and start and end dates.
CalcStatClusterGivenCenter

Calls the function to obtain the cluster with the maximum log-likelihood ratio or minimum DIC of all the clusters with the same center and start and end dates.
computeprob

Computes the probability that a model parameter is <=k from inla marginals
SelectStatsAllClustersNoOverlap

Removes the overlapping clusters.
CreateGridDClusterm

Creates grid over the study area.
NY8

Leukemia in an eight-county region of upstate New York, 1978-1982.
DetectClustersModel

Detects clusters and computes their significance.
Navarre

Brain cancer in males in Navarre, Spain, 1988-1994.