.validate_custom_locations

Helper function: given a data frame, and strings for label_var,
lat_var, and long_var, the df is checked for

internal

Provides utilities for manipulating time series of location-based counts of events to detect geo-spatial clusters. Significance of these clusters is determined using a set of models that classify based on a learned relationship between observed and the log(observed/expected) ratio of counts. The approach implemented here is similar to prospective space-time estimation of clusters using the scan statistic.

Luke Mullany

gsClusterDetect

Utilities for Geo-Spatial Cluster Detection and Significance
Classification

Howard Burkom

.validate_custom_locations function

<dl><dt>df</dt>
<dd>A <code>data.frame</code> containing label and coordinate columns.</dd>
<dt>label_var</dt>
<dd>Character scalar naming the label column.</dd>
<dt>lat_var</dt>
<dd>Character scalar naming the latitude column.</dd>
<dt>long_var</dt>
<dd>Character scalar naming the longitude column.</dd></dl>

Arguments

Helper function: given a data frame, and strings for label_var,
lat_var, and long_var, the df is checked for — .validate_custom_locations

<dl>

<dt>df</dt>
<dd>A <code>data.frame</code> containing label and coordinate columns.</dd>


<dt>label_var</dt>
<dd>Character scalar naming the label column.</dd>


<dt>lat_var</dt>
<dd>Character scalar naming the latitude column.</dd>


<dt>long_var</dt>
<dd>Character scalar naming the longitude column.</dd>

</dl>

.validate_custom_locations: Helper function: given a data frame, and strings for label_var, lat_var, and long_var, the df is checked for

Description

Usage

Value

Arguments