hpipy.price_model.HedonicModel

class hpipy.price_model.HedonicModel(hpi_data, **kwargs)

Bases: BaseHousePriceModel

Hedonic house price model.

Methods

__init__	Initialize base house price model.
fit	Fit the hedonic model and generate index coefficients.

Attributes

coefficients
model_obj
periods
base_price
params

Parameters:

• hpi_data (TransactionData)

• kwargs (Any)

fit(estimator='base', log_dep=True, dep_var=None, ind_var=None, **kwargs)

Fit the hedonic model and generate index coefficients.

Parameters:

• estimator (str, optional) – Estimator type. One of “base”, “robust”, or “weighted”. Defaults to “base”.

• log_dep (bool, optional) – Log transform the dependent variable. Defaults to True.

• dep_var (str | None, optional) – Dependent variable. Defaults to None.

• ind_var (list[str] | None, optional) – Independent variable(s). Defaults to None.

• kwargs (Any)

Returns:

The hedonic house price model.

Return type:

Self

__init__(hpi_data, **kwargs)

Initialize base house price model.

Parameters:

• hpi_data (TransactionData)

• kwargs (Any)

Return type:

None

coefficients: DataFrame

model_obj: Any

periods: DataFrame

base_price: float

params: dict[str, Any]