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README.md

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In the final line, `ngmodel` produces rather a lot of output, but is useful to see all of the outputs produced by the `fronpy.estimate`. For example, we can see that `ngmodel.lnlikelihood` would give us the log-likelihood, `ngmodel.beta` would give us the estimated frontier parameters, `ngmodel.eff_bc` would give us E[e^(-U_i)|E_i=ε_i] for each observation, and so on. Note that currently, `fronpy.estimate` requires a `numpy.ndarray` with rows representing observations and columns representing variables, where:
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- all data are numeric.
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- the first column contains the dependent variable and the remaining columns.
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- the first column contains the dependent variable.
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- columns 2,...,n contain the independent variables, including a constant if desired.
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- there are no missing, `NaN`, `inf`, `-inf` or similarly invalid values.
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The package then assumes that the frontier is linear in its parameters, e.g. Cobb-Douglas or translog; note that any interactions must be included as columns in the `numpy.ndarray`. The package may be generalised in future to allow for arbitrary functional forms.

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