
kappa
$\kappa$.dfisher(r, kappa = 1, nu = NULL, Haar = TRUE) pfisher(q, kappa = 1, nu = NULL, lower.tail = TRUE)
rfisher(n, kappa = 1, nu = NULL)
length(n)>1
,
the length is taken to be the number required.kappa
.r <- seq(-pi, pi, length = 500)
#Visualize the matrix Fisher density fucntion with respect to the Haar measure
plot(r, dfisher(r, kappa = 10), type = 'l', ylab = 'f(r)')
#Visualize the matrix Fisher density fucntion with respect to the Lebesgue measure
plot(r, dfisher(r, kappa = 10, Haar = FALSE), type = 'l', ylab = 'f(r)')
#Plot the matrix Fisher CDF
plot(r,pfisher(r,kappa = 10), type = 'l', ylab = 'F(r)')
#Generate random observations from matrix Fisher distribution
rs <- rfisher(20, kappa = 1)
hist(rs, breaks = 10)
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