surveillance (version 1.5-4)

algo.summary: Summary Table Generation for Several Disease Chains

Description

Summary table generation for several disease chains.

Usage

algo.summary(compMatrices)

Arguments

compMatrices

list of matrices constructed by algo.compare.

Value

• matrix
  summing up the singular input matrices

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.

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) )