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# EXAMPLE1 (CF of the uniform von Mises distribution on (-pi,pi))
t <- seq(-10, 10, length.out = 501)
plotGraf(function(t)
cfC_vonMises(t), t, title = "CF of the uniform von Mises distribution on (-pi,pi)")
# EXAMPLE2 (CF of the mixture of the von Mises distribution on (-pi,pi))
mu1 <- 0
kappa1 <- 5
mu2 <- 1
kappa2 <- 15
cf <-
function(t)
0.25 * cfC_vonMises(t, mu1, kappa1) + 0.75 * cfC_vonMises(t, mu2, kappa2)
t <- seq(-10, 10, length.out = 501)
plotGraf(cf, t, title = "CF of the mixture of the von Mises distribution")
# EXAMPLE3 (PDF/CDF of the von Mises distribution on (-pi,pi))
mu <- 0
kappa <- 5
cf <- function(t)
cfC_vonMises(t, mu, kappa)
result <- cf2DistGP(cf, xMin = -pi, xMax = pi)
angle <- result$x
radius <- result$pdf
plotPolar(angle, radius)
# EXAMPLE4 (PDF/CDF of the linear combinantion of 2 von Mises distribution on (-pi,pi))
mu1 <- 0
kappa1 <- 5
mu2 <- 1
kappa2 <- 15
cf <-
function(t)
cfC_vonMises(1 * t, mu1, kappa1) * cfC_vonMises(0.25 * t, mu2, kappa2)
result <- cf2DistGP(cf,
xMin = -pi,
xMax = pi,
isCircular = TRUE)
angle <- result$x
radius <- result$pdf
plotPolar(angle, radius)
# EXAMPLE5 (PDF/CDF of the mixture of the von Mises distribution on (0,2*pi))
mu1 <- 0
kappa1 <- 5
mu2 <- 1
kappa2 <- 15
mu3 <- pi
kappa3 <- 10
cf <-
function(t)
0.25 * cfC_vonMises(t, mu1, kappa1) + 0.25 * cfC_vonMises(t, mu2, kappa2) + 0.5 *
cfC_vonMises(t, mu3, kappa3)
result <- cf2DistGP(cf,
xMin = 0,
xMax = 2 * pi,
isCircular = TRUE)
angle <- result$x
radius <- result$pdf
plotPolar(angle, radius)
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