scaling

scaling,Toc-method

scale the 'Hits' and 'Hits+FalseAlarms' values in the TOC output table, as well as the prevalence and population, using a scaling factor. Labels for the modified units in the TOC object are changed to <code>newUnits</code>

methods

spatial

Construction of the Total Operating Characteristic (TOC) Curve and the Receiver (aka Relative) Operating Characteristic (ROC) Curve for spatial and non-spatial data. The TOC method is a modification of the ROC method which measures the ability of an index variable to diagnose either presence or absence of a characteristic. The diagnosis depends on whether the value of an index variable is above a threshold. Each threshold generates a two-by-two contingency table, which contains four entries: hits (H), misses (M), false alarms (FA), and correct rejections (CR). While ROC shows for each threshold only two ratios, H/(H + M) and FA/(FA + CR), TOC reveals the size of every entry in the contingency table for each threshold (Pontius Jr., R.G., Si, K. 2014. <doi:10.1080/13658816.2013.862623>).

Al� Santacruz

Total Operating Characteristic Curve and ROC Curve

scaling function

<dl> <dt>x</dt>
<dd>an object of class Toc</dd> <dt>scalingFactor</dt>
<dd>numeric value to scale 'Hits' and 'Hits+FalseAlarms' values in the TOC output table, as well as the prevalence and population</dd> <dt>newUnits</dt>
<dd>charater string for the new data units in the TOC object</dd></dl>

Arguments

scale the output TOC values and change units — scaling

<dl>

 <dt>x</dt>
<dd>an object of class Toc</dd>

 <dt>scalingFactor</dt>
<dd>numeric value to scale 'Hits' and 'Hits+FalseAlarms' values in the TOC output table, as well as the prevalence and population</dd>

 <dt>newUnits</dt>
<dd>charater string for the new data units in the TOC object</dd>

</dl>

scaling: scale the output TOC values and change units

Description

Usage

Value

Arguments

See Also

Examples