The paper presents the estimate for the total variation distance between the distribution of the number of appearances of homogeneous disjoint events in a segment of strongly ergodic Markov chain on the finite state space and accompanying Poisson distribution (i.e., Poisson distribution with a parameter equal to the expectation of the random variable under consideration). For this purpose the Chen-Stein method was used. As a result Poisson and normal limit theorems for the number of events appearances are derived. The considered scheme describes the well-known number of runs on consecutive letters, the number of -recurrent runs, etc., and can be used for describing the properties of distribution of the special form scan statistic.
You will need Adobe Acrobat reader. For more information and free download of the reader, please follow this link.
References
[1] D.L. Antzoulakos, S. Chadjiconstantinidis, Distributions of numbers of
success runs of fixed length in Markov dependent trials, Ann. Inst. Statist.
Math., 53, No 3 (2001), 599–619.
[2] N. Balakrishnan, M.V. Koutras, Runs and Scans with Applications,
Whiley, New York (2002).
[3] A.D. Barbour, L. Holst, S. Janson, Poisson Approximation, Oxford Univ.
Press, Oxford (1992).
[4] O. Chryssaphinou, S. Papastavridis, E. Vaggelatou, Poisson approximation
for the number of non-overlapping appearances of several words in Markov
chain, Combinatorics Probab., 10 (2001), 293–308.
[5] O. Chryssaphinou, E. Vaggelatou, Compound Poisson approximation for
multiple runs in a Markov chain, Ann. Inst. Statist. Math., 54, No 2 (2002),
411–424.
[6] P. Erdos, P. Revesz, On the length of the longest head-run, In: Topics in
Information Theory. Colloquia Math. Soc. J. Bolyai 16, Keszthely, Hungary
(1975), 219–228.
[7] W. Feller, An Introduction to Probability Theory and Its Applications,
Vol. I, 3rd Ed., Wiley, New York (1968).
[8] J.C. Fu, Distribution theorem of runs and patterns associated with a sequence
of multi-state trials, Statist. Sinica, 6 (1996), 957–974.
[9] J.C. Fu, W.Y.W. Lou, Z.-D. Bai, G. Li, The exact and limiting distributions
for the number of successes in success runs within a sequence of
Markov-dependent two-state trials, Ann. Inst. Statist. Math., 54, No 4
(2002), 719–730.
[10] J. Glaz, V. Pozdnyakov, S. Wallenstein (Eds.), Scan Statistics. Methods
and Applications, Birkh¨auser, Boston-Basel-Berlin (2009).
[11] K. Inoue, S. Aki, Joint distributions of numbers of runs of specified length
in a sequence of Markov dependent multistate trials, Ann. Inst. Statist.
Math., 59, No 3 (2007), 577–595.
[12] J.G. Kemeny, J.L. Snell, Finite Markov Chains, Springer-Verlag, New York
(1976).
[13] W.Y.W. Lou, On runs and longest runs tests: a method of finite Markov
chain imbedding, J. Amer. Statist. Assoc., 91 (1996), 1595–1601.
[14] N.M. Mezhennaya, Limit theorems for the number of dense series in a
random sequence, Discrete Mathematics and Applications, 19, No 2 (2009),
215–228.
[15] N.M. Mezhennaya, Limit theorems for dense F-recurrent series and chains
numbers in sequence of independent random variables, Herald of the Bauman
Moscow State Technical University, Series Natural Sciences, 3 (2014),
11–25 (in Russian).
[16] V.G. Mikhailov, On the limit theorem of B.A. Sevastiyanov for sums of dependent
random indicators, Review of Applied and Industrial Mathematics,
10, No 3 (2003), 571–578 (in Russian).
[17] V.G. Mikhailov, On asymptotic properties of the number of runs of events,
Tr. Diskr. Mat., 9 (2006), 152–163 (in Russian).
[18] V.G. Mikhailov, Estimates of accuracy of the Poisson approximation for
the distribution of number of runs of long string repetitions in a Markov
chain, Discrete Math. Appl., 26, No 2 (2016), 105–113.
[19] V.G. Mikhailov, On the probability of existence of substrings with the same
structure in a random sequence Discrete Math. Appl., 27, No 6 (2017),
377–386.
[20] V.G. Mikhailov, A.M. Shoitov, On multiple repetitions of long tuples in a
Markov chain, Mat. Vopr. Kriptogr., 6, No 3 (2015), 117–133 (in Russian).
[21] V.G. Mikhailov, A.M. Shoitov, On repetitions of long tuples in a Markov
chain, Discrete Math. Appl., 25, No 5 (2015), 295–303.
[22] A.A. Minakov, Poisson approximation for the number of non-decreasing
runs in Markov chains, Mat. Vopr. Kriptogr., 9, No 2 (2018), 103–116.
[24] L.Ya. Savelyev, S.V. Balakin, Some applications of the stochastic theory
of runs, Sib. Zh. Ind. Mat., 15, No 3 (2012), 111–123 (in Russian).
[25] M.I. Tikhomirova, Limit distributions of the number of absent chains of
identical outcomes, Discrete Math. Appl., 18, No 3 (2008), 293–300.
[26] E. Vaggelatou, On the length of the longest run in a multi-state Markov
chain, Statist. Probab. Letters, 62 (2003), 211–221.
[27] Y.Z. Zhang, X.Y. Wu, Some results associated with the longest run in a
strongly ergodicMarkov chain, Acta Mathematica Sinica, 29, No 10 (2013),
1939–1948.