tfprobability: sts_decompose_forecast_by_component – R documentation

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tfprobability

sts_decompose_forecast_by_component

Decompose a forecast distribution into contributions from each component.

Description

Decompose a forecast distribution into contributions from each component.

Usage

sts_decompose_forecast_by_component(model, forecast_dist, parameter_samples)

Arguments

`model`	An instance of `sts_sum` representing a structural time series model.
`forecast_dist`	A `Distribution` instance returned by `sts_forecast()`. (specifically, must be a `tfd.MixtureSameFamily` over a `tfd_linear_gaussian_state_space_model` parameterized by posterior samples).
`parameter_samples`	`list` of `tensors` representing posterior samples of model parameters, with shapes `list(tf$concat(list(list(num_posterior_draws), param<1>$prior$batch_shape, param<1>$prior$event_shape), list(list(num_posterior_draws), param<2>$prior$batch_shape, param<2>$prior$event_shape), ... ) )` for all model parameters. This may optionally also be a named list mapping parameter names to `tensor` values.

Value

component_dists A named list mapping component StructuralTimeSeries instances (elements of model$components) to Distribution instances representing the marginal forecast for each component. Each distribution has batch shape matching forecast_dist (specifically, the event shape is [num_steps_forecast]).