Simulating inhomogeneous Poisson process without loop

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A reproducible example would help, have you tried FOREACH

On Jul 3, 2011, at 7:53 AM, Tristan Linke <tristan.linke at gmail.com>  
wrote:
Dear all

I want to simulate a stochastic jump variance process in which N is
Bernoulli (Poisson approximation) with intensity lambda0 + lambda1*Vt.
lambda0 is constant and lambda1 can be interpreted as a regression
coefficient on the current variance level Vt. J is the scaling factor

How can I rewrite this avoiding the loop structure which is very
time-consuming for long simulations?

for (i in 1:N){
...
N <- rbinom(n=1, size=1, prob=(lambda0+lambda1*Vt))
Vt <- ... + J*N
..
}

P.S. This is going towards the Duffie, Pan, Singleton 2000 Transform  
Pricing
paper, here stochastic volatility with state-dependent correlated  
jumps
(Eraker 2004).

Thanks a lot in advance.

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dt=.01;
t=seq(0, .5, by=dt)
apply(matrix(t),  1,  function (x)  { rbinom(1,1,prob=x  )} )

would produce a  series of Bernoulli trials with success probability t  
\in  [0, .5].
  In my humble opinion, this style is more pertinent in terms of the 
programming logic of R although I am not very sure about the efficiency.

All the best.
A reproducible example would help, have you tried FOREACH

On Jul 3, 2011, at 7:53 AM, Tristan Linke <tristan.linke at gmail.com> 
wrote:

Dear all

I want to simulate a stochastic jump variance process in which N is
Bernoulli (Poisson approximation) with intensity lambda0 + lambda1*Vt.
lambda0 is constant and lambda1 can be interpreted as a regression
coefficient on the current variance level Vt. J is the scaling factor

How can I rewrite this avoiding the loop structure which is very
time-consuming for long simulations?

for (i in 1:N){
...
N <- rbinom(n=1, size=1, prob=(lambda0+lambda1*Vt))
Vt <- ... + J*N
..
}

P.S. This is going towards the Duffie, Pan, Singleton 2000 Transform 
Pricing
paper, here stochastic volatility with state-dependent correlated jumps
(Eraker 2004).

Thanks a lot in advance.

   [[alternative HTML version deleted]]