Sim
Functions for simulating data associated with a Markov process given an appropriate transition kernel.
Value members
Concrete methods
A function for producing a very simple plot of a time series, useful for a quick eye-balling of simulation output. Called purely for the side-effect of rendering a plot on the console.
A function for producing a very simple plot of a time series, useful for a quick eye-balling of simulation output. Called purely for the side-effect of rendering a plot on the console.
- Value Params
- title
Optional figure title
- ts
A time series of
States
Simulate multiple independent realisations from a transition kernel
Simulate multiple independent realisations from a transition kernel
- Value Params
- deltat
The time interval over which to simulate the process
- n
The number of realisations required
- stepFun
The transition kernel to use
- t0
The intial time
- x0
The initial state
- Returns
A
Listof realisations of the kernel at timet0+deltat
Use a transition kernel to simulate states on an irregular time grid
Use a transition kernel to simulate states on an irregular time grid
- Value Params
- stepFun
The transition kernel, such as output by one of the functions in
Sim- t0
Initial time
- timeList
A list of times where the state of the process is required
- x0
Initial state
- Returns
A time series of simulated states at the required times corresponding to a single realisation of the underlying stochastic process
Utility for converting a time series to a CSV string
Utility for converting a time series to a CSV string
- Value Params
- ts
A time series of
States
- Returns
A CSV string
Use a transition kernel to simulate states on a regular time grid
Use a transition kernel to simulate states on a regular time grid
- Value Params
- dt
The time step of the output time grid
- stepFun
The transition kernel, such as output by one of the functions in
Sim- t0
Initial time
- tt
The terminal time
- x0
Initial state
- Returns
A time series of simulated states corresponding to a single realisation of the underlying stochastic process