InstrumentalVariableRegression.check_start_vals

InstrumentalVariableRegression.check_start_vals(start)

Check that the starting values for MCMC do not cause the relevant log probability to evaluate to something invalid (e.g. Inf or NaN)

Parameters:

start (dict, or array of dict) – Starting point in parameter space (or partial point) Defaults to trace.point(-1)) if there is a trace provided and model.initial_point if not (defaults to empty dict). Initialization methods for NUTS (see init keyword) can overwrite the default.

Raises:

• KeyError` if the parameters provided by start do not agree with th –

• parameters contained within the model. –

• pymc.exceptions.SamplingError` if the evaluation of the parameter –

• in start leads to an invalid (i.e. non-finite) state –

Return type:

None