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Summary table generation for several disease chains.

Usage

algo.summary(compMatrices)

Arguments

compMatrices

list of matrices constructed by algo.compare.

Value

a 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.

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) )