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mou.loglik()
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Loglikelihood for multivariate Ornstein-Uhlenbeck process. |
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msde-package
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msde: Bayesian Inference for Multivariate Stochastic Differential Equations |
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mvn.hyper.check()
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Argument checking for the default multivariate normal prior. |
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sde.diff()
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SDE diffusion function. |
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sde.drift()
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SDE drift function. |
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sde.examples()
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Example SDE models. |
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sde.init()
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MCMC initialization. |
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sde.loglik()
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SDE loglikelihood function. |
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sde.make.model()
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Create an SDE model object. |
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sde.post()
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MCMC sampler for the SDE posterior. |
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sde.prior()
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SDE prior function. |
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sde.sim()
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Simulation of multivariate SDE trajectories. |
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sde.valid.data() sde.valid.params()
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SDE data and parameter validators. |