/

SimulateGaussianMixture

[this page | pdf]

Returns an array providing simulated output from a multivariate time series model of the world involving one or more states or regimes, each of which is characterised by a Gaussian (i.e. multivariate normal) distribution, with a Markov chain process indicating how likely it is to move between each state over a given time period. The output is 2 dimensional, with the first dimension characterising the simulation and the time period and the second dimension providing a vector of the variables themselves.

 

Models where each state itself consists of a predefined (distributional) mixture of multivariate normal distributions can be accommodated in such a model by defining the Markov chain appropriately.

 

The function includes parameters that:

 

(a)    define the starting state or how it may itself be simulated

(b)   include a random number seed so that the results can be reproduced subsequently

(c)    include sampling algorithms that help to reduce run times by sampling in a uniform manner across the quantile range that the individual random variables can take

 

---

NAVIGATION LINKS
Contents | Prev | Next

---

-          Interactively run function

-          Interactive instructions

-          Example calculation

-          Output type / Parameter details

-          Illustrative spreadsheet

-          Other Markov processes functions

-          Computation units used

Note: If you use any Nematrian web service either programmatically or interactively then you will be deemed to have agreed to the Nematrian website License Agreement

---