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  • Getting Started
  • Guide
  • Example Gallery
  • How We Compare
  • API
  • Contributing
  • About PyMC Labs

Section Navigation

  • bass
    • data
      • to_bass_dataset
    • model
      • F
      • create_bass_model
      • f
      • BassModel
      • BassPriors
  • causal_utils
    • same_markov_equivalence_class_CPdag
  • clv
    • distributions
      • BetaGeoBetaBinom
      • BetaGeoNBD
      • ModifiedBetaGeoNBD
      • ParetoNBD
      • ShiftedBetaGeometric
    • models
      • basic
        • CLVModel
      • beta_geo
        • BetaGeoModel
      • beta_geo_beta_binom
        • BetaGeoBetaBinomModel
      • gamma_gamma
        • BaseGammaGammaModel
        • GammaGammaModel
        • GammaGammaModelIndividual
      • modified_beta_geo
        • ModifiedBetaGeoModel
      • pareto_nbd
        • ParetoNBDModel
      • shifted_beta_geo
        • ShiftedBetaGeoModel
        • ShiftedBetaGeoModelIndividual
    • plotting
      • plot_customer_exposure
      • plot_expected_purchases_over_time
      • plot_expected_purchases_ppc
      • plot_frequency_recency_matrix
      • plot_probability_alive_matrix
    • utils
      • customer_lifetime_value
      • rfm_segments
      • rfm_summary
      • rfm_train_test_split
      • to_xarray
  • customer_choice
    • consideration_set_logit
      • ConsiderationInstruments
      • ConsiderationSetMixedLogit
    • maxdiff
      • prepare_maxdiff_data
      • MaxDiffArrays
      • MaxDiffMixedLogit
    • mixed_logit
      • MixedLogit
    • mnl_logit
      • MNLogit
    • mv_its
      • plot_product
      • MVITS
    • nested_logit
      • NestedLogit
    • synthetic_data
      • generate_maxdiff_conjoint_data
      • generate_maxdiff_data
      • generate_saturated_data
      • generate_unsaturated_data
  • data
    • fivetran
      • process_fivetran_ad_reporting
      • process_fivetran_shopify_unique_orders
      • FivetranAccessor
    • idata
      • mmm_wrapper
        • MMMIDataWrapper
      • schema
        • InferenceDataGroupSchema
        • MMMIdataSchema
        • VariableSchema
      • utils
        • aggregate_idata_dims
        • aggregate_idata_time
        • filter_idata_by_dates
        • filter_idata_by_dims
        • get_posterior_predictive
        • get_prior
        • get_prior_predictive
        • idata_from_zarr
        • idata_to_zarr
        • subsample_draws
  • hsgp_kwargs
    • CovFunc
    • HSGPKwargs
  • metrics
    • crps
    • nmae
    • nrmse
    • per_observation_crps
  • mlflow
    • autolog
    • create_log_callback
    • load_mmm
    • log_arviz_summary
    • log_error
    • log_inference_data
    • log_likelihood_type
    • log_metadata
    • log_mmm
    • log_mmm_configuration
    • log_mmm_evaluation_metrics
    • log_model_derived_info
    • log_model_graph
    • log_sample_diagnostics
    • log_types_of_parameters
    • log_versions
    • MMMWrapper
  • mmm
    • additive_effect
      • additive_effect
        • safe_to_datetime
        • EventAdditiveEffect
        • FourierEffect
        • LinearTrendEffect
        • Model
        • MuEffect
      • frequency_reach_effect
        • FrequencyReachAdditiveEffect
    • budget_optimizer
      • optimizer_xarray_builder
      • BudgetOptimizer
      • BuildMergedModel
      • CustomModelWrapper
      • OptimizerCompatibleModelWrapper
    • builders
      • factories
        • build
        • locate
        • resolve
      • schema
        • suggest_typo_fix
        • BuildSpec
        • CalibrationStep
        • DataConfig
        • MMMYamlConfig
      • yaml
        • build_mmm_from_yaml
    • causal
      • BuildModelFromDAG
      • CausalGraphModel
      • TBFPC
      • TestResult
    • components
      • adstock
        • adstock_from_dict
        • AdstockTransformation
        • BinomialAdstock
        • DelayedAdstock
        • GeometricAdstock
        • NoAdstock
        • WeibullCDFAdstock
        • WeibullPDFAdstock
      • base
        • Transformation
      • saturation
        • saturation_from_dict
        • HillSaturation
        • HillSaturationSigmoid
        • HillShapeSaturation
        • InverseScaledLogisticSaturation
        • LogSaturation
        • LogisticSaturation
        • MichaelisMentenSaturation
        • NoSaturation
        • RootSaturation
        • SaturationTransformation
        • TanhSaturation
        • TanhSaturationBaselined
    • constraints
      • build_default_sum_constraint
      • compile_constraints_for_scipy
      • Constraint
    • decomposition
      • identity_counterfactual_component
      • log_counterfactual_remove_component
      • original_scale_prediction_from_mu
      • safe_proportional_share
    • dims
    • evaluation
      • calculate_metric_distributions
      • compute_summary_metrics
      • summarize_metric_distributions
    • events
      • days_from_reference
      • AsymmetricGaussianBasis
      • Basis
      • EventEffect
      • GaussianBasis
      • HalfGaussianBasis
    • fourier
      • generate_fourier_modes
      • FourierBase
      • MonthlyFourier
      • WeeklyFourier
      • YearlyFourier
    • hsgp
      • approx_hsgp_hyperparams
      • create_complexity_penalizing_prior
      • create_constrained_inverse_gamma_prior
      • create_eta_prior
      • create_m_and_L_recommendations
      • HSGP
      • HSGPBase
      • HSGPPeriodic
      • PeriodicCovFunc
      • SoftPlusHSGP
    • incrementality
      • Incrementality
    • lift_test
      • add_cost_per_target_observations
      • add_cost_per_target_potentials
      • add_lift_measurements_to_likelihood_from_saturation
      • add_saturation_observations
      • assert_is_subset
      • assert_monotonic
      • create_time_varying_saturation
      • exact_row_indices
      • scale_channel_lift_measurements
      • scale_lift_measurements
      • scale_target_for_lift_measurements
    • linear_regression
      • FancyLinearRegression
    • linear_trend
      • LinearTrend
    • link
      • get_link_spec
      • IdentityLinkSpec
      • LinkFunction
      • LinkSpec
      • LogLinkSpec
    • media_transformation
      • MediaConfig
      • MediaConfigList
      • MediaTransformation
    • mmm
      • create_sample_kwargs
      • BudgetOptimizerWrapper
      • MMM
    • multidimensional
    • plot
      • MMMPlotSuite
    • plot_interactive
      • MMMPlotlyFactory
    • plotting
      • budget
        • BudgetPlots
      • cv
        • MMMCVPlotSuite
      • decomposition
        • DecompositionPlots
      • diagnostics
        • DiagnosticsPlots
      • sensitivity
        • SensitivityPlots
      • suite
        • MMMPlotSuiteFacade
      • transformations
        • TransformationPlots
    • preprocessing
      • preprocessing_method_X
      • preprocessing_method_y
      • MaxAbsScaleChannels
      • MaxAbsScaleTarget
      • StandardizeControls
    • scaling
      • deserialize_variable_scaling
      • panel_channel_fixed_scaling_remaining_dims
      • validate_fixed_scaling_keys
      • DataDerivedScaling
      • FixedScaling
      • Scaling
      • VariableScaling
    • sensitivity_analysis
      • SensitivityAnalysis
    • summary
      • MMMSummaryFactory
    • time_slice_cross_validation
      • TimeSliceCrossValidationResult
      • TimeSliceCrossValidator
    • transformers
      • batched_convolution
      • binomial_adstock
      • delayed_adstock
      • geometric_adstock
      • hill_function
      • hill_saturation_sigmoid
      • inverse_scaled_logistic_saturation
      • logistic_saturation
      • michaelis_menten
      • root_saturation
      • tanh_saturation
      • tanh_saturation_baselined
      • weibull_adstock
      • ConvMode
      • TanhSaturationBaselinedParameters
      • TanhSaturationParameters
      • WeibullType
    • tvp
      • create_hsgp_from_config
      • create_time_varying_gp_multiplier
      • infer_time_index
      • is_hsgp_kwargs_format
      • time_varying_prior
    • types
      • MMMBuilder
    • utility
      • adjusted_value_at_risk_score
      • average_response
      • conditional_value_at_risk
      • diversification_ratio
      • mean_tightness_score
      • portfolio_entropy
      • raroc
      • sharpe_ratio
      • tail_distance
      • value_at_risk
    • utils
      • add_noise_to_channel_allocation
      • apply_sklearn_transformer_across_dim
      • build_contributions
      • cdf
      • create_index
      • create_new_spend_data
      • create_zero_dataset
      • density
      • transform_1d_array
    • validating
      • validation_method_X
      • validation_method_y
      • ValidateChannelColumns
      • ValidateControlColumns
      • ValidateDateColumn
      • ValidateTargetColumn
  • model_builder
    • create_idata_accessor
    • create_sample_kwargs
    • requires_model
    • ModelBuilder
    • ModelIO
    • RegressionModelBuilder
  • model_config
    • parse_model_config
  • model_graph
    • deterministics_to_flat
    • get_symbolic_rv_shape
  • paths
    • create_data_url
    • URLPath
  • pie
    • model
      • PIEModel
  • plot
    • create_legend_handles
    • drop_scalar_coords
    • generate_colors
    • get_plot_coords
    • get_total_coord_size
    • plot_curve
    • plot_hdi
    • plot_samples
    • random_samples
    • selections
    • set_subplot_kwargs_defaults
  • prior
    • deserialize_alternative_prior
    • is_alternative_prior
  • pytensor_utils
    • extract_response_distribution
    • merge_models
    • validate_unique_value_vars
    • ModelSamplerEstimator
  • serialization
    • DeferredFactory
    • DeserializationContext
    • Serializable
    • SerializableBaseModel
    • TypeRegistry
  • serialization_migration
    • main
    • migrate_idata
  • special_priors
    • LaplacePrior
    • LogNormalPrior
    • MaskedPrior
    • SpecialPrior
  • utils
    • from_netcdf
  • API
  • mmm
  • link
  • LogLinkSpec
  • LogLinkSpec.inverse_link

LogLinkSpec.inverse_link#

LogLinkSpec.inverse_link(mu)[source]#

Return exp(mu) (the conditional median of the LogNormal response).

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  • LogLinkSpec.inverse_link()
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