data_measurements/notes

For zipf:
    # TODO: Incorporate this function (not currently using)
    def fit_others(self, fit):
        st.markdown(
            "_Checking log likelihood ratio to see if the data is better explained by other well-behaved distributions..._"
        )
        # The first value returned from distribution_compare is the log likelihood ratio
        better_distro = False
        trunc = fit.distribution_compare("power_law", "truncated_power_law")
        if trunc[0] < 0:
            st.markdown("Seems a truncated power law is a better fit.")
            better_distro = True

        lognormal = fit.distribution_compare("power_law", "lognormal")
        if lognormal[0] < 0:
            st.markdown("Seems a lognormal distribution is a better fit.")
            st.markdown("But don't panic -- that happens sometimes with language.")
            better_distro = True

        exponential = fit.distribution_compare("power_law", "exponential")
        if exponential[0] < 0:
            st.markdown("Seems an exponential distribution is a better fit. Panic.")
            better_distro = True

        if not better_distro:
            st.markdown("\nSeems your data is best fit by a power law. Celebrate!!")