rsCIR {sde}R Documentation

Cox-Ingersoll-Ross process stationary law

Description

Density, distribution function, quantile function and random generation for the stationary law of for the Cox-Ingersoll-Ross process

Usage

dsCIR(x, theta, log = FALSE)
psCIR(x, theta, lower.tail = TRUE, log.p = FALSE) 
qsCIR(p, theta, lower.tail = TRUE, log.p = FALSE)
rsCIR(n=1, theta)

Arguments

x vector of quantiles.
p vector of probabilities.
theta parameter of the Ornstein-Uhlenbeck process. See details.
n number of random numbers to generate from the conditional distribution.
log, log.p logical; if TRUE, probabilities p are given as log(p).
lower.tail logical; if TRUE (default), probabilities are P[X <= x], otherwise, P[X > x].

Details

This function returns quantities related to the stationary law of the process solution of dX_t = (theta[1] - theta[2]*Xt)*dt + theta[3]*sqrt(X_t)*dWt.

Constraints: 2*theta[1] > theta[3]^2, theta's>0.

Value

x a numeric vector

Note

This package is a companion to the book Simulation and Inference for Stochastic Differential Equation, Springer, NY.

Author(s)

Stefano Maria Iacus

References

Cox, J.C., Ingersoll, J.E., Ross, S.A. (1985) A theory of the term structure of interest rates, Econometrica, 53, 385-408.

See Also

rsCIR

Examples

rsCIR(n=1, theta=c(6,2,1))

[Package sde version 1.8 Index]