tfp.edward2.LinearGaussianStateSpaceModel

Create a random variable for LinearGaussianStateSpaceModel.

See LinearGaussianStateSpaceModel for more details.

RandomVariable.

Original Docstring for Distribution

Initialize a LinearGaussianStateSpaceModel.

num_timesteps Integer Tensor total number of timesteps.
transition_matrix A transition operator, represented by a Tensor or LinearOperator of shape [latent_size, latent_size], or by a callable taking as argument a scalar integer Tensor t and returning a Tensor or LinearOperator representing the transition operator from latent state at time t to time t + 1.
transition_noise An instance of tfd.MultivariateNormalLinearOperator with event shape [latent_size], representing the mean and covariance of the transition noise model, or a callable taking as argument a scalar integer Tensor t and returning such a distribution representing the noise in the transition from time t to time t + 1.
observation_matrix An observation operator, represented by a Tensor or LinearOperator of shape [observation_size, latent_size], or by a callable taking as argument a scalar integer Tensor t and returning a timestep-specific Tensor or LinearOperator.
observation_noise An instance of tfd.MultivariateNormalLinearOperator with event shape [observation_size], representing the mean and covariance of the observation noise model, or a callable taking as argument a scalar integer Tensor t and returning a timestep-specific noise model.
initial_state_prior An instance of MultivariateNormalLinearOperator representing the prior distribution on latent states; must have event shape [latent_size].
initial_step optional int specifying the time of the first modeled timestep. This is added as an offset when passing timesteps t to (optional) callables specifying timestep-specific transition and observation models.
validate_args Python bool, default False. Whether to validate input with asserts. If validate_args is False, and the inputs are invalid, correct behavior is not guaranteed.
allow_nan_stats Python bool, default True. If False, raise an exception if a statistic (e.g. mean/mode/etc...) is undefined for any batch member If True, batch members with valid parameters leading to undefined statistics will return NaN for this statistic.
name The name to give Ops created by the initializer.