expert (version 1.0-0)

mean.expert: Arithmetic Mean of the Expert Aggregated Distribution

Description

Mean of objects of class "expert".

Usage

"mean"(x, ...)

Arguments

x

an object of class "expert".

...

further arguments passed to or from other methods.

Value

A numeric value.

Details

The mean of a distribution with probabilities $p[1], \dots, p[r]$ on intervals defined by the boundaries $c[1], \dots, c[r]$ is $$\sum_{j = 1}^r \frac{c_{j - 1} + c_j}{2}\, p_j.$$

References

Klugman, S. A., Panjer, H. H. and Willmot, G. E. (1998), Loss Models, From Data to Decisions, Wiley.

See Also

expert to create objects of class "expert"

Examples

x <- list(E1 <- list(A1 <- c(0.14, 0.22, 0.28),
                     A2 <- c(130000, 150000, 200000),
                     X <- c(350000, 400000, 525000)),
          E2 <- list(A1 <- c(0.2, 0.3, 0.4),
                     A2 <- c(165000, 205000, 250000),
                     X <- c(550000, 600000, 650000)),
          E3 <- list(A1 <- c(0.2, 0.4, 0.52),
                     A2 <- c(200000, 400000, 500000),
                     X <- c(625000, 700000, 800000)))
probs <- c(0.1, 0.5, 0.9)
true.seed <- c(0.27, 210000)
fit <- expert(x, "cooke", probs, true.seed, 0.03)
mean(fit)