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A B C D E F I L M N O P R S T V
| pomp-package | Partially-observed Markov processes |
| as-method | Methods of the "pomp" class |
| bspline.basis | B-spline bases |
| coef-method | Methods of the "pomp" class |
| coef-pomp | Methods of the "pomp" class |
| coef<- | Methods of the "pomp" class |
| coef<--method | Methods of the "pomp" class |
| coef<--pomp | Methods of the "pomp" class |
| coerce-method | Methods of the "pomp" class |
| compare.mif | Methods of the "mif" class |
| continue | The MIF algorithm |
| continue-method | The MIF algorithm |
| continue-mif | The MIF algorithm |
| conv.rec | Methods of the "mif" class |
| conv.rec-method | Methods of the "mif" class |
| conv.rec-mif | Methods of the "mif" class |
| data.array | Methods of the "pomp" class |
| data.array-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-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-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 | Plug-ins for dynamical models based on stochastic Euler algorithms |
| euler.simulate | Plug-ins for dynamical models based on stochastic Euler algorithms |
| euler.sir | Seasonal SIR model implemented as an Euler-multinomial model |
| eulermultinom | Euler-multinomial models |
| filter.mean | Methods of the "mif" class |
| filter.mean-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-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-method | Methods of the "mif" class |
| logLik-mif | Methods of the "mif" class |
| LondonYorke | Reported cases of chickenpox, measles, and mumps from Baltimore and New York, 1928-1972 |
| mif | The MIF algorithm |
| mif-class | The "mif" class |
| mif-method | The MIF algorithm |
| 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) |
| onestep.density | Plug-ins for dynamical models based on stochastic Euler algorithms |
| onestep.simulate | Plug-ins for dynamical models based on stochastic Euler algorithms |
| ou2 | Two-dimensional Ornstein-Uhlenbeck process |
| particles | Generate particles from the user-specified distribution. |
| particles-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-method | Particle filter |
| pfilter-mif | Particle filter |
| pfilter-pomp | Particle filter |
| plot-method | Methods of the "mif" class |
| plot-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-method | Methods of the "mif" class |
| pred.mean-mif | Methods of the "mif" class |
| pred.var | Methods of the "mif" class |
| pred.var-method | Methods of the "mif" class |
| pred.var-mif | Methods of the "mif" class |
| print-method | Methods of the "pomp" class |
| print-pomp | Methods of the "pomp" class |
| profile.design | Design matrices for likelihood slices and profiles |
| reulermultinom | Euler-multinomial models |
| rmeasure | Simulate the measurement model of a partially-observed Markov process |
| rmeasure-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-method | Simulate the process model of a partially-observed Markov process |
| rprocess-pomp | Simulate the process model of a partially-observed Markov process |
| rw2 | Two-dimensional random-walk process |
| show-method | Methods of the "pomp" class |
| show-pomp | Methods of the "pomp" class |
| simulate-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-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. |
| slice.design | Design matrices for likelihood slices and profiles |
| sobol | Sobol' low-discrepancy sequence |
| states | Methods of the "pomp" class |
| states-method | Methods of the "pomp" class |
| states-pomp | Methods of the "pomp" class |
| time-method | Methods of the "pomp" class |
| time-pomp | Methods of the "pomp" class |
| time<- | Methods of the "pomp" class |
| time<--method | Methods of the "pomp" class |
| time<--pomp | Methods of the "pomp" class |
| traj.match | Trajectory matching |
| trajectory | Compute trajectories of the determinstic skeleton. |
| trajectory-method | Compute trajectories of the determinstic skeleton. |
| trajectory-pomp | Compute trajectories of the determinstic skeleton. |
| verhulst | Simple Verhulst-Pearl (logistic) model. |