pymare.estimators.estimators.BaseEstimator

class BaseEstimator

Bases: object

A base class for Estimators.

abstract fit(*args, **kwargs)

Fit the estimator to data.

fit_dataset(dataset, *args, **kwargs)

Apply the current estimator to the passed Dataset container.

A convenience interface that wraps fit() and automatically aligns the variables held in a Dataset with the required arguments.

Parameters:

• dataset (Dataset) – A PyMARE Dataset instance holding the data.

• *args – Optional positional arguments to pass onto the fit() method.

• **kwargs – Optional keyword arguments to pass onto the fit() method.

get_v(dataset)

Get the variances, or an estimate thereof, from the given Dataset.

Parameters:

dataset (Dataset) – The dataset to use to retrieve/estimate v.

Returns:

2-dimensional array of variances/variance estimates.

Return type:

numpy.ndarray

Notes

This is equivalent to directly accessing dataset.v when variances are present, but affords a way of estimating v from sample size (n) for any estimator that implicitly estimates a sigma^2 parameter.

summary()

Generate a MetaRegressionResults object for the fitted estimator.

Return type:

MetaRegressionResults

Examples using pymare.estimators.estimators.BaseEstimator

The Basics of Running a Meta-Analysis

The Basics of Running a Meta-Analysis

Run Estimators on a simulated dataset

Run Estimators on a simulated dataset