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import wooldridge as woo

import statsmodels.formula.api as smf

import statsmodels.stats.outliers_influence as smo

hprice1 = woo.dataWoo('hprice1')

# original linear regression:

reg = smf.ols(formula='price ~ lotsize + sqrft + bdrms', data=hprice1)

results = reg.fit()

# automated RESET test:

reset_output = smo.reset_ramsey(res=results, degree=3)

fstat_auto = reset_output.statistic[0][0]

fpval_auto = reset_output.pvalue

print(f'fstat_auto: {fstat_auto}\n')

print(f'fpval_auto: {fpval_auto}\n')