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actuar (version 3.3-4)

elev: Empirical Limited Expected Value

Description

Compute the empirical limited expected value for individual or grouped data.

Usage

elev(x, ...)

# S3 method for default elev(x, ...)

# S3 method for grouped.data elev(x, ...)

# S3 method for elev print(x, digits = getOption("digits") - 2, ...)

# S3 method for elev summary(object, ...)

# S3 method for elev knots(Fn, ...)

# S3 method for elev plot(x, ..., main = NULL, xlab = "x", ylab = "Empirical LEV")

Value

For elev, a function of class "elev", inheriting from the

"function" class.

Arguments

x

a vector or an object of class "grouped.data" (in which case only the first column of frequencies is used); for the methods, an object of class "elev", typically.

digits

number of significant digits to use, see print.

Fn, object

an R object inheriting from "ogive".

main

main title.

xlab, ylab

labels of x and y axis.

...

arguments to be passed to subsequent methods.

Author

Vincent Goulet vincent.goulet@act.ulaval.ca and Mathieu Pigeon

Details

The limited expected value (LEV) at \(u\) of a random variable \(X\) is \(E[X \wedge u] = E[\min(X, u)]\). For individual data \(x_1, \dots, x_n\), the empirical LEV \(E_n[X \wedge u]\) is thus $$E_n[X \wedge u] = \frac{1}{n} \left( \sum_{x_j < u} x_j + \sum_{x_j \geq u} u \right).$$

Methods of elev exist for individual data or for grouped data created with grouped.data. The formula in this case is too long to show here. See the reference for details.

References

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

See Also

grouped.data to create grouped data objects; stepfun for related documentation (even though the empirical LEV is not a step function).

Examples

Run this code
data(gdental)
lev <- elev(gdental)
lev
summary(lev)
knots(lev)            # the group boundaries

lev(knots(lev))       # empirical lev at boundaries
lev(c(80, 200, 2000)) # and at other limits

plot(lev, type = "o", pch = 16)

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