algo.quality: Computation of Quality Values for a Surveillance System...

In jimhester/surveillance: Temporal and Spatio-Temporal Modeling and Monitoring of Epidemic Phenomena

Description

Computation of the quality values for a surveillance System output.

Usage

    algo.quality(survResObj, penalty = 20)

Arguments

survResObj	object of class survRes, which includes the state chain and the computed alarm chain
penalty	the maximal penalty for the lag

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,\code{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.

Value

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.

See Also

algo.compare

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)

jimhester/surveillance documentation built on May 19, 2019, 10:33 a.m.