Information Criterion and Scan Statistic Approach for Detecting
Multiple Disease Clusters
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Documentation for package ‘multiflexscan’ version 0.2.0
Help Pages
| multiflexscan-package | Detecting multiple spatial disease clusters using the information criterion and scan statistic approach |
| AIC.multiflexscan | AIC and BIC for the selected cluster model |
| as.data.frame.multiflexscan | Coerce selected clusters to a data frame |
| BIC.multiflexscan | AIC and BIC for the selected cluster model |
| choropleth | Draw a choropleth map of multiflexscan clusters |
| clusters | Cluster summary table |
| coef.multiflexscan | Extract selected cluster summaries |
| get_setting | Analysis settings |
| multiflexscan | Detect multiple spatial clusters using the flexible/circular scan statistic |
| nclusters | Number of clusters selected by the information criterion |
| nobs.multiflexscan | Number of regions in the analysis |
| plot.multiflexscan | Plot method for the 'multiflexscan' object. The neighborhood graph is drawn with 'igraph', following 'plot.rflexscan()'. |
| print.multiflexscan | Print multiflexscan object |
| print.summary.multiflexscan | Print summary of multiflexscan results |
| pvalue | Overall Monte Carlo p-value |
| summary.multiflexscan | Summarizing multiflexscan results |