Large deviation asymptotics for occupancy problems

被引:15
作者
Dupuis, P [1 ]
Nuzman, C
Whiting, P
机构
[1] Brown Univ, Lefschetz Ctr Dynam Studies, Providence, RI 02912 USA
[2] Bell Labs, Murray Hill, NJ 07974 USA
关键词
occupancy problems; urn models; large deviations; calculus of variations; sample paths; explicit solutions; combinatorics; Euler-Lagrange equations;
D O I
10.1214/009117904000000135
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
In the standard formulation of the occupancy problem one considers the distribution of r balls in n cells, with each ball assigned independently to a given cell with probability 1/n. Although closed form expressions can be given for the distribution of various interesting quantities (such as the fraction of cells that contain a given number of balls), these expressions are often of limited practical use. Approximations provide an attractive alternative, and in the present paper we consider a large deviation approximation as r and n tend to infinity. In order to analyze the problem we first consider a dynamical model, where the balls are placed in the cells sequentially and "time" corresponds to the number of balls that have already been thrown. A complete large deviation analysis of this "process level" problem is carried out, and the rate function for the original problem is then obtained via the contraction principle. The variational problem that characterizes this rate function is analyzed, and a fairly complete and explicit solution is obtained. The minimizing trajectories and minimal cost are identified up to two constants, and the constants are characterized as the unique solution to an elementary fixed point problem. These results are then used to solve a number of interesting problems, including an overflow problem and the partial coupon collector's problem.
引用
收藏
页码:2765 / 2818
页数:54
相关论文
共 28 条
  • [1] [Anonymous], 1977, URN MODELS THEIR APP
  • [2] Explicit solutions for variational problems in the quadrant
    Avram, F
    Dai, JG
    Hasenbein, JJ
    [J]. QUEUEING SYSTEMS, 2001, 37 (1-3) : 259 - 289
  • [3] BARTON DE, 1959, BIOMETRIKA, V46, P218, DOI 10.2307/2332824
  • [4] BARTON DE, 1959, J ROY STAT SOC B, V21, P120
  • [5] Bertsekas D., 2019, Reinforcement Learning and Optimal Control
  • [6] Billingsley P, 1968, CONVERGE PROBAB MEAS
  • [7] BOUCHERON S, 2002, ANN APPL PROBAB, V2, P1
  • [8] Bucklew J. A., 1990, Large Deviations Techniques in Decision, Simulation, and Estimation
  • [9] Cesari L., 1983, OPTIMIZATION THEORY
  • [10] CHARALAMBIDES A, 1997, ADV COMBINATORIAL ME, P259