Index _ | A | C | E | F | G | I | K | L | O | P | R | S | T | V _ __init__() (aimz.ImpactModel method) (aimz.utils.data.ArrayDataset method) (aimz.utils.data.ArrayLoader method) A ArrayDataset (class in aimz.utils.data) ArrayLoader (class in aimz.utils.data) autolog() (in module aimz.mlflow) C cleanup() (aimz.ImpactModel method) cleanup_models() (aimz.ImpactModel class method) E estimate_effect() (aimz.ImpactModel method) F fit() (aimz.ImpactModel method) fit_on_batch() (aimz.ImpactModel method) G get_default_conda_env() (in module aimz.mlflow) get_default_pip_requirements() (in module aimz.mlflow) I ImpactModel (class in aimz) inference (aimz.ImpactModel property) is_fitted() (aimz.ImpactModel method) K kernel (aimz.ImpactModel property) kernel_spec (aimz.ImpactModel property) KernelSpec (class in aimz.model) L load_model() (in module aimz.mlflow) log_likelihood() (aimz.ImpactModel method) log_model() (in module aimz.mlflow) O output_observed (aimz.model.KernelSpec attribute) P pad_array() (aimz.utils.data.ArrayLoader method) param_input (aimz.ImpactModel property) param_output (aimz.ImpactModel property) posterior (aimz.ImpactModel property) predict() (aimz.ImpactModel method) predict_on_batch() (aimz.ImpactModel method) R return_sites (aimz.model.KernelSpec attribute) rng_key (aimz.ImpactModel property) S sample() (aimz.ImpactModel method) sample_posterior_predictive() (aimz.ImpactModel method) sample_posterior_predictive_on_batch() (aimz.ImpactModel method) sample_prior_predictive() (aimz.ImpactModel method) sample_prior_predictive_on_batch() (aimz.ImpactModel method) sample_sites (aimz.model.KernelSpec attribute) save_model() (in module aimz.mlflow) set_posterior_sample() (aimz.ImpactModel method) T temp_dir (aimz.ImpactModel property) traced (aimz.model.KernelSpec attribute) train_on_batch() (aimz.ImpactModel method) V vi_result (aimz.ImpactModel property)