algo.summary: Summary Table Generation for Several Disease Chains

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

Description

Summary table generation for several disease chains.

Usage

        algo.summary(compMatrices)

Arguments

compMatrices

list of matrices constructed by algo.compare.

Details

As lag the mean of all single lags is returned. TP values, FN values, TN values and FP values are summed up. dist, sens and spec are new computed on the basis of the new TP value, FN value, TN value and FP value.

Value

matrix

summing up the singular input matrices

See Also

algo.compare, algo.quality

Examples

    # Create a test object
    disProgObj1 <- sim.pointSource(p = 0.99, r = 0.5, length = 400,
                            A = 1, alpha = 1, beta = 0, phi = 0,
                            frequency = 1, state = NULL, K = 1.7)
    disProgObj2 <- sim.pointSource(p = 0.99, r = 0.5, length = 400,
                            A = 1, alpha = 1, beta = 0, phi = 0,
                            frequency = 1, state = NULL, K = 5)
    disProgObj3 <- sim.pointSource(p = 0.99, r = 0.5, length = 400,
                            A = 1, alpha = 1, beta = 0, phi = 0,
                            frequency = 1, state = NULL, K = 17)

    # Let this object be tested from any methods in range = 200:400
    range <- 200:400
    control <- list( list(funcName = "rki1", range = range),
                    list(funcName = "rki2", range = range),
                    list(funcName = "rki3", range = range)
                )

    compMatrix1 <- algo.compare(algo.call(disProgObj1, control=control))
    compMatrix2 <- algo.compare(algo.call(disProgObj2, control=control))
    compMatrix3 <- algo.compare(algo.call(disProgObj3, control=control))

    algo.summary( list(a=compMatrix1, b=compMatrix2, c=compMatrix3) )

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