gauss.hermite | R Documentation |
Calculates an approximation to the expected value of any function of a normally-distributed random variable, using Gauss-Hermite quadrature.
gauss.hermite(f, mu = 0, sd = 1, ..., order = 5)
f |
The function whose moment should be approximated. |
mu |
Mean of the normal distribution. |
sd |
Standard deviation of the normal distribution. |
... |
Additional arguments passed to |
order |
Number of quadrature points in the Gauss-Hermite quadrature approximation. A small positive integer. |
This algorithm calculates the approximate expected value of
f(Z)
when Z
is a normally-distributed random
variable with mean mu
and standard deviation sd
.
The expected value is an integral with respect to the
Gaussian density; this integral is approximated
using Gauss-Hermite quadrature.
The argument f
should be a function in the R language
whose first argument is the variable Z
. Additional arguments
may be passed through ...
. The value returned by f
may be a single numeric value, a vector, or a matrix. The values
returned by f
for different values of Z
must have
compatible dimensions.
The result is a weighted average of several values of f
.
Numeric value, vector or matrix.
, \rolf
and \ege.
gauss.hermite(function(x) x^2, 3, 1)
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