We prove a general central limit theorem for probabilities of large deviations for sequences of random variables satisfying certain analytic conditions. This theorem has wide applications to combinatorial structures and to the distribution of additive arithmetical functions. The method of proof is an extension of Kubilius' version of Cramér's classical method based on analytic moment generating functions. We thus generalize Cramér's and Kubilius's theorems on large deviations.
Hsien-Kuei Hwang. "Large deviations for combinatorial distributions. I. Central limit theorems." Ann. Appl. Probab. 6 (1) 297 - 319, February 1996. https://doi.org/10.1214/aoap/1034968075