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

Section Navigation

bass
- model
  - F
  - create_bass_model
  - f
  - BassPriors
causal_utils
- same_markov_equivalence_class_CPdag
clv
customer_choice
data
- fivetran
- idata
hsgp_kwargs
- CovFunc
- HSGPKwargs
metrics
- crps
- nmae
- nrmse
- per_observation_crps
mlflow
mmm
model_builder
model_config
- parse_model_config
model_graph
- deterministics_to_flat
- get_symbolic_rv_shape
paths
- create_data_url
- URLPath
plot
prior
- deserialize_alternative_prior
- is_alternative_prior
pytensor_utils
serialization
serialization_migration
- main
- migrate_idata
special_priors
utils
- from_netcdf

API
mmm
additive_effect
LinearTrendEffect
LinearTrendEffect.from_dict

LinearTrendEffect.from_dict#

classmethod LinearTrendEffect.from_dict(data)[source]#: Reconstruct from a dict, using registry for nested LinearTrend.

On this page

LinearTrendEffect.from_dict()

Consulting and training

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