| 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!!") |