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This module contains functions that compare the goodness of fit of a distribution/curve to data or the fit of two distributions/curves to each other.

nll(data, model) Negative log likelihood given data and a model
lrt(data, model_full, model_reduced[, df]) Compare two nested models using a likelihood ratio test
AIC(data, model[, params, corrected]) Akaike Information Criteria given data and a model
AIC_compare(aic_list) Calculates delta AIC and AIC weights from a list of AIC values
sum_of_squares(obs, pred) Sum of squares between observed and predicted data
r_squared(obs, pred[, one_to_one, log_trans]) R^2 value for a regression of observed and predicted data
preston_bin(data, max_num) Bins data on base 2 using Preston’s method