Public instance methods
IDictionary<object, object> generate(int number_of_series, int series_length, IDictionary<IGraphNodeBase, object> model_parameters, object seed, object add_observation_noise)
object generate_dyn(object number_of_series, object series_length, object model_parameters, object seed, object add_observation_noise)
object get_broadcasted_observation_model_dyn(object times)
Tensor get_features_for_timesteps(object timesteps)
object get_features_for_timesteps_dyn(object timesteps)
Tensor get_observation_noise_covariance(double minimum_initial_variance)
Tensor get_state_transition_noise_covariance(double minimum_initial_variance)
Tensor get_state_transition_noise_covariance_(double minimum_initial_variance)
object per_step_batch_loss(IDictionary<object, object> features, object mode, IEnumerable<object> state)
object per_step_batch_loss(IDictionary<object, object> features, object mode, IGraphNodeBase state)
object per_step_batch_loss(IDictionary<object, object> features, object mode, PythonClassContainer state)
object per_step_batch_loss(IDictionary<object, object> features, object mode, object state)
object per_step_batch_loss(object features, object mode, IEnumerable<object> state)
object per_step_batch_loss(object features, object mode, IGraphNodeBase state)
object per_step_batch_loss(object features, object mode, object state)
object per_step_batch_loss_dyn(object features, object mode, object state)
Public properties
object ar_coefs get; set;
IList<object> exogenous_feature_columns get;
object exogenous_feature_columns_dyn get;
object ma_coefs get; set;
int num_features get; set;
object prior_state_mean get; set;
object prior_state_var get; set;
object state_dimension get; set;
int state_num_blocks get; set;