algo.summary: Summary Table Generation for Several Disease Chains

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

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.

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

a 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) )

surveillance documentation built on Nov. 2, 2023, 6:05 p.m.