Description Usage Arguments Author(s) References See Also Examples
This function computes the estimation of the density associated to the jump rate for a piecewise-deterministic Markov process whose state space is finite. The estimator is given in the paper mentioned in References.
1 | CondPdf.DC(dat,x,t,h,alpha,bound)
|
dat |
data from which the estimator is to be computed. It corresponds to the observation of a process within a long time. dat is a matrix such that the last column contains the interarrival times, while the other columns contain the states. |
x |
the conditional probability density function is estimated given state=x. |
t |
the conditional probability density function is estimated at time t. In addition, t must be less than bound. |
h |
bandwith |
alpha |
strictly positive real number. If h is NULL, the bandwith is 1/n^alpha where n is the number of data. |
bound |
the estimator is computed as an integral between the times 0 and bound. bound must be less than the deterministic exit time function tstar computed at state x |
Romain Azais
Azais R., Dufour F., and Gegout-Petit A. Nonparametric estimation of the conditional distribution of the inter-jumping times for piecewise-deterministic Markov processes Scandinavian Journal of Statistics, 2014.
CondPdf.DC.interval
, Simu.PDMP.DC
1 2 3 4 5 6 7 | # CondPdf.DC
# Simulation of a PDMP with discrete state space
dat<-Simu.PDMP.DC(1,200,verbose=FALSE)
# Estimation of the conditional density given state=2 at time 2
CondPdf.DC(dat,2,2,bound=5.8)
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