| ghypParam | R Documentation |
These objects store different parameter sets of the generalized hyperbolic distribution as matrices for testing or demonstration purposes.
The parameter sets ghypSmallShape and
ghypLargeShape have a constant location parameter of
\mu = 0, and constant scale parameter \delta =
1. In ghypSmallParam and ghypLargeParam the values of
the location and scale parameters vary. In these parameter sets the
location parameter \mu = 0 takes values from {0, 1} and
{-1, 0, 1, 2} respectively. For the scale parameter
\delta, values are drawn from {1, 5} and {1, 2, 5,
10} respectively.
For the shape parameters \alpha and \beta the
approach is more complex. The values for these shape parameters were
chosen by choosing values of \xi and \chi which
range over the shape triangle, then the function ghypChangePars
was applied to convert them to the \alpha, \beta
parameterization. The resulting \alpha, \beta
values were then rounded to three decimal places. See the examples for
the values of \xi and \chi for the large
parameter sets.
The values of \lambda are drawn from {-0.5, 0, 1} in
ghypSmallShape and {-1, -0.5, 0, 0.5, 1, 2} in
ghypLargeShape.
ghypSmallShape
ghypLargeShape
ghypSmallParam
ghypLargeParam
ghypSmallShape: a 22 by 5 matrix;
ghypLargeShape: a 90 by 5 matrix;
ghypSmallParam: a 84 by 5 matrix;
ghypLargeParam: a 1440 by 5 matrix.
David Scott d.scott@auckland.ac.nz
data(ghypParam)
plotShapeTriangle()
xis <- rep(c(0.1,0.3,0.5,0.7,0.9), 1:5)
chis <- c(0,-0.25,0.25,-0.45,0,0.45,-0.65,-0.3,0.3,0.65,
-0.85,-0.4,0,0.4,0.85)
points(chis, xis, pch = 20, col = "red")
## Testing the accuracy of ghypMean
for (i in 1:nrow(ghypSmallParam)) {
param <- ghypSmallParam[i, ]
x <- rghyp(1000, param = param)
sampleMean <- mean(x)
funMean <- ghypMean(param = param)
difference <- abs(sampleMean - funMean)
print(difference)
}
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