# Computation of Quality Values for a Surveillance System Result

`algo.quality.Rd`

Computation of the quality values for a surveillance system output.

## Arguments

- sts
object of class

`survRes`

or`sts`

, which includes the state chain and the computed alarm chain- penalty
the maximal penalty for the lag

## Value

a list of quality values:

- TP
Number of correct found outbreaks.

- FP
Number of false found outbreaks.

- TN
Number of correct found non outbreaks.

- FN
Number of false found non outbreaks.

- sens
True positive rate, meaning TP/(FN + TP).

- spec
True negative rate, meaning TN/(TN + FP).

- dist
Euclidean distance between (1-spec, sens) to (0,1).

- lag
Lag of the outbreak recognizing by the system.

## Details

The lag is defined as follows:
In the state chain just the beginnings of an outbreak chain (outbreaks directly
following each other) are considered. In the alarm chain, the range from the beginning
of an outbreak until `min(`next outbreak beginning`, penalty)`

timepoints is considered. The `penalty`

timepoints were
chosen, to provide an upper bound on the penalty for not discovering an outbreak. Now the difference between the first alarm by the system and the defined beginning is denoted ``the lag'' Additionally outbreaks found by the system are not
punished. At the end, the mean of the lags for every outbreak chain is returned
as summary lag.

## Examples

```
# Create a test object
disProgObj <- sim.pointSource(p = 0.99, r = 0.5, length = 200, A = 1,
alpha = 1, beta = 0, phi = 0,
frequency = 1, state = NULL, K = 1.7)
# Let this object be tested from rki1
survResObj <- algo.rki1(disProgObj, control = list(range = 50:200))
# Compute the quality values
algo.quality(survResObj)
```