Summary Table Generation for Several Disease Chains
algo.summary.Rd
Summary table generation for several disease chains.
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) )