The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
We generated \(n=200\) observations from the uniform distribution on \(S^{d-1}\), with \(d=3\), and \(\rho = 0.7\).
library(QuadratiK)
n <- 200
d <- 3
set.seed(2468)
z <- matrix(rnorm(n * d), n, d)
dat_sphere <- z/sqrt(rowSums(z^2))
The pk.test
is used for testing uniformity of the
generated sample.
##
## Poisson Kernel-based quadratic distance test of Uniformity on the Sphere
## Selected consentration parameter rho: 0.7
##
## U-statistic:
##
## H0 is rejected: FALSE
## Statistic Un: -0.9756673
## Critical value: 0.02660107
##
## V-statistic:
##
## H0 is rejected: FALSE
## Statistic Vn: 14.89598
## Critical value: 23.22949
The summary
method for the pk.test
output
object provides the results of the performed test, and generates a
figure showing the qq-plots against the uniform distribution of each
variable with a table of standard descriptive statistics.
##
## Poisson Kernel-based quadratic distance test of Uniformity on the Sphere
## Test_Statistics Critical_Value Reject_H0
## 1 -0.9756673 0.02660107 FALSE
## 2 14.8959834 23.22948694 FALSE
The figure automatically generated by the summary
function on the result of the test for uniformity displays the qq-plots
between the given samples and the uniform distribution with a table of
the standard descriptive statistics for each variable.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.