von_mises_sim {SOPIE}

Generates Simulated Data from a Von Mises Distribution with Noise

Description

Generates simulated data over the interval [0; 1] from a scaled Von Mises distribution with noise.

Usage

von_mises_sim(n = 5000, k = 1, c = 0.3, noise = 0.2)

Arguments

n

number of random variates in the simulated data set.

k

concentration parameter \kappa of the Von Mises distribution.

c

the point of truncation of the Von Mises distribution. The value of c represent that value in the interval [0; c] and [1-c; 1] where the Von Mises density is remove, i.e. f(\theta) = 0 for \theta \in [0 ; c] and \theta \in [1-c ; 1] where f(\theta) is the Von Mises density function.

noise

proportion of random noise to include in the simulated data set. If n random variates are required, then \lfloor (1-noise)n \rfloor values are generated from the Von Mises density and the remainder from an uniform density.

Value

The output vector of this function is n random variates in the interval [0; 1] from a scaled Von Mises density with uniform noise proportional to noise.

Author(s)

Willem Daniel Schutte

References

Jammalamadaka, S. Rao and SenGupta, A. (2001). Topics in Circular Statistics, World Scientific Publishing Co. Pte. Ltd.
Robert CP, Casella G (2010). Introducing Monte Carlo methods with R. Springer.
Schutte WD (2014). Nonparametric estimation of the off-pulse interval(s) of a pulsar light curve. Ph.D. thesis, North-West University. URL http://hdl.handle.net/10394/12199

See Also

pvonmises

Examples

set.seed(777)
simdata<-von_mises_sim(n=5000,k=1,c=0.3,noise=0.2)
hist(simdata)
SOPIE(simdata,h=1,to=1,alpha=0.05,g=5,r=10,m=1,grid=100)