SimulateGaussianMixture
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Function Description
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
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Output type / Parameter details

Illustrative spreadsheet

Other Markov processes functions

Computation units used
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