pomp-package |
Partially-observed Markov processes |
as,pomp-method |
Methods of the "pomp" class |
bspline.basis |
B-spline bases |
coef,pomp-method |
Methods of the "pomp" class |
coef-pomp |
Methods of the "pomp" class |
coef<-,pomp-method |
Methods of the "pomp" class |
coef<--pomp |
Methods of the "pomp" class |
coerce,pomp,data.frame-method |
Methods of the "pomp" class |
compare.mif |
Methods of the "mif" class |
continue |
The MIF algorithm |
continue,mif-method |
The MIF algorithm |
continue-mif |
The MIF algorithm |
conv.rec |
Methods of the "mif" class |
conv.rec,mif-method |
Methods of the "mif" class |
conv.rec-mif |
Methods of the "mif" class |
data.array |
Methods of the "pomp" class |
data.array,pomp-method |
Methods of the "pomp" class |
data.array-pomp |
Methods of the "pomp" class |
deulermultinom |
Euler-multinomial models |
dmeasure |
Evaluate the probability density of observations given underlying states in a partially-observed Markov process |
dmeasure,pomp-method |
Evaluate the probability density of observations given underlying states in a partially-observed Markov process |
dmeasure-pomp |
Evaluate the probability density of observations given underlying states in a partially-observed Markov process |
dprocess |
Evaluate the probability density of state transitions in a Markov process |
dprocess,pomp-method |
Evaluate the probability density of state transitions in a Markov process |
dprocess-pomp |
Evaluate the probability density of state transitions in a Markov process |
euler |
Dynamical models based on stochastic Euler algorithms |
eulermultinom |
Euler-multinomial models |
filter.mean |
Methods of the "mif" class |
filter.mean,mif-method |
Methods of the "mif" class |
filter.mean-mif |
Methods of the "mif" class |
init.state |
Return a matrix of initial conditions given a vector of parameters and an initial time. |
init.state,pomp-method |
Return a matrix of initial conditions given a vector of parameters and an initial time. |
init.state-pomp |
Return a matrix of initial conditions given a vector of parameters and an initial time. |
logLik,mif-method |
Methods of the "mif" class |
logLik-mif |
Methods of the "mif" class |
mif |
The MIF algorithm |
mif,mif-method |
The MIF algorithm |
mif,pomp-method |
The MIF algorithm |
mif-class |
The "mif" class |
mif-methods |
Methods of the "mif" class |
mif-mif |
The MIF algorithm |
mif-pomp |
The MIF algorithm |
nlf |
Fit Model to Data Using Nonlinear Forecasting (NLF) |
ou2 |
Two-dimensional Ornstein-Uhlenbeck process |
particles |
Generate particles from the user-specified distribution. |
particles,mif-method |
Generate particles from the user-specified distribution. |
particles-mif |
Generate particles from the user-specified distribution. |
periodic.bspline.basis |
B-spline bases |
pfilter |
Particle filter |
pfilter,mif-method |
Particle filter |
pfilter,pomp-method |
Particle filter |
pfilter-mif |
Particle filter |
pfilter-pomp |
Particle filter |
plot,mif-method |
Methods of the "mif" class |
plot,pomp-method |
Methods of the "pomp" class |
plot-mif |
Methods of the "mif" class |
plot-pomp |
Methods of the "pomp" class |
pomp |
Partially-observed Markov process object. |
pomp-class |
Partially-observed Markov process |
pomp-methods |
Methods of the "pomp" class |
pred.mean |
Methods of the "mif" class |
pred.mean,mif-method |
Methods of the "mif" class |
pred.mean-mif |
Methods of the "mif" class |
pred.var |
Methods of the "mif" class |
pred.var,mif-method |
Methods of the "mif" class |
pred.var-mif |
Methods of the "mif" class |
print,pomp-method |
Methods of the "pomp" class |
print-pomp |
Methods of the "pomp" class |
reulermultinom |
Euler-multinomial models |
rmeasure |
Simulate the measurement model of a partially-observed Markov process |
rmeasure,pomp-method |
Simulate the measurement model of a partially-observed Markov process |
rmeasure-pomp |
Simulate the measurement model of a partially-observed Markov process |
rprocess |
Simulate the process model of a partially-observed Markov process |
rprocess,pomp-method |
Simulate the process model of a partially-observed Markov process |
rprocess-pomp |
Simulate the process model of a partially-observed Markov process |
show,pomp-method |
Methods of the "pomp" class |
show-pomp |
Methods of the "pomp" class |
simulate,pomp-method |
Running simulations of a partially-observed Markov process |
simulate-pomp |
Running simulations of a partially-observed Markov process |
skeleton |
Evaluate the deterministic skeleton at the given points in state space. |
skeleton,pomp-method |
Evaluate the deterministic skeleton at the given points in state space. |
skeleton-pomp |
Evaluate the deterministic skeleton at the given points in state space. |
sobol |
Sobol' low-discrepancy sequence |
states |
Methods of the "pomp" class |
states,pomp-method |
Methods of the "pomp" class |
states-pomp |
Methods of the "pomp" class |
time,pomp-method |
Methods of the "pomp" class |
time-pomp |
Methods of the "pomp" class |
trajectory |
Compute trajectories of the determinstic skeleton. |
trajectory,pomp-method |
Compute trajectories of the determinstic skeleton. |
trajectory-pomp |
Compute trajectories of the determinstic skeleton. |