Summary Table Generation for Several Disease Chains
Summary table generation for several disease chains.
algo.summary(compMatrices)
compMatrices |
list of matrices constructed by algo.compare. |
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.
a matrix summing up the singular input matrices
# 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) )Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.