linearmodels.panel.model.RandomEffects

class RandomEffects(dependent, exog, *, weights=None)[source]

One-way Random Effects model for panel data

Parameters
dependentarray_like

Dependent (left-hand-side) variable (time by entity)

exogarray_like

Exogenous or right-hand-side variables (variable by time by entity).

weightsarray_like, optional

Weights to use in estimation. Assumes residual variance is proportional to inverse of weight to that the residual time the weight should be homoskedastic.

Notes

The model is given by

\[y_{it} = \beta^{\prime}x_{it} + u_i + \epsilon_{it}\]

where \(u_i\) is a shock that is independent of \(x_{it}\) but common to all entities i.

Methods

fit(self, \*, small_sample, cov_type, …)

from_formula(formula, data, numpy.ndarray, …)

Create a model from a formula

predict(self, params, …)

Predict values for additional data

reformat_clusters(self, clusters, …)

Reformat cluster variables

Properties

formula

Formula used to construct the model

has_constant

Flag indicating the model a constant or implicit constant

not_null

Locations of non-missing observations