expectedCost {BookEKM} | R Documentation |
Calculates expected costs, Section 8.1.2, by an asymptotic approach
expectedCost(mu.1.log, sd.1.log, mu.2.log, sd.2.log, n, L.L = 1/10000, L.H = 10000, odds = 1, c.D = 0.1)
mu.1.log |
Expected value of log(X1) |
sd.1.log |
Standard deviation of log(X1) |
mu.2.log |
Expected value of log(X2) |
sd.2.log |
Standard deviation of log(X2) |
n |
Number of markers assumed iid |
L.L |
Lower bound |
L.H |
Upper bound |
odds |
Prior odds |
c.D |
Cost of aqcuiring data |
p1 |
First probability in formula for V |
p2 |
Second probability in formula for V |
p3 |
Third probability in formula for V |
p4 |
Fourth probability in formula for V |
ExpectedCost |
Expected cost |
Thore Egeland <Thore.Egeland@nmbu.no>
require(Familias) data(NorwegianFrequencies) p <- as.double(NorwegianFrequencies[1][[1]]) L <- length(p) m <- LRmoments2(p, kappaP = c(0.5,0.5,0), kappaD = c(1,0,0), logg = TRUE)$moments[c(1,3,5,7)] m <- as.double(m) expectedCost(m[1], m[2],m[3], m[4], n=25, L.L=1/100, L.H =100, odds = 1 , c.D = 0.1)