Abstract:
Integral large deviation theorems are obtained for multidimensional hypergeometric distribution. These theorems allow us to evaluate the probabilities of large deviations with the remainder term of order $O(1/N)$. The corresponding hypergeometric distribution of a random vector $(\mu_1,\dots,\mu_s)$ has the form
$$
\mathbf{P}\{(\mu_1,\dots,\mu_s)=(k_1,\dots,k_s)\}=\frac{C_{M_1}^{k_1}\dotsb C_{M_s}^{k_s}}{C_N^n}\,,
$$
and $k_j\le M_j$, $j=1,\dots,s$; 0 in the remaining cases.
Keywords:saddle-point method, hypergeometric distribution, large deviations, asymptotic estimates.