# A chi-square goodness-of-fit test for continuous distributions against a known alternative

@article{Rolke2021ACG, title={A chi-square goodness-of-fit test for continuous distributions against a known alternative}, author={Wolfgang Rolke and Cristian Gutierrez Gongora}, journal={Comput. Stat.}, year={2021}, volume={36}, pages={1885-1900} }

The chi square goodness-of-fit test is among the oldest known statistical tests, first proposed by Pearson in 1900 for the multinomial distribution. It has been in use in many fields ever since. However, various studies have shown that when applied to data from a continuous distribution it is generally inferior to other methods such as the Kolmogorov-Smirnov or Anderson-Darling tests. However, the performance, that is the power, of the chi square test depends crucially on the way the data is…

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