yuima (version 1.15.27)

setPPR: Point Process

Description

Constructor of a Point Process Regression Model

Usage

setPPR(yuima, counting.var = "N", gFun, Kernel,
  var.dx = "s", var.dt = "s", lambda.var = "lambda",
  lower.var = "0", upper.var = "t", nrow = 1, ncol = 1)

Value

An object of yuima.PPR

Arguments

yuima

an object of yuima.model-class that describes the mathematical features of counting and covariates processes Y[t]=(X[t],N[t]).

counting.var

a label denoting the name of the counting process.

gFun

a vector string that is the mathematical expression of the vector function g(t,Y[t-],theta) in the intensity process.

Kernel

a matrix string that is the kernel kappa(t-s,Y[s],theta) in the definition of the intensity process.

var.dx

a string denoting the integration variable in the intensity process.

var.dt

a string denoting the integration time variable in the intensity process.

lambda.var

name of the intensity process.

lower.var

Lower bound of the support for the integral in the definition of the intensity process.

upper.var

Upper bound of the support for the integral in the definition of the intensity process.

nrow

number of rows in the kernel.

ncol

number of columns in the kernel.

Author

The YUIMA Project Team

Contacts: Lorenzo Mercuri

References

Insert Here References

Examples

if (FALSE) {
## Hawkes process with power law kernel

# I. Law Definition:
my.rHwk2 <- function(n){
  as.matrix(rep(1,n))
  }
Law.Hwk2 <- setLaw(rng = my.rHwk2, dim = 1)

# II. Definition of the counting process N_t
mod.Hwk2 <- setModel(drift = c("0"), diffusion = matrix("0",1,1),
  jump.coeff = matrix(c("1"),1,1), measure = list(df = Law.Hwk2),
  measure.type = "code", solve.variable = c("N"),
  xinit=c("0"))

# III. Definition of g() and kappa()
g.Hwk2 <- "mu"
Kern.Hwk2 <- "alpha/(1+(t-s))^beta"

# IV. Construction of an yuima.PPR object
PPR.Hwk2 <- setPPR(yuima = mod.Hwk2, gFun=g.Hwk2,
  Kernel = as.matrix(Kern.Hwk2),var.dx = "N")
}