For a class of stationary Markov-dependent sequences (An, Bn)∈ℝ2, we consider the random linear recursion Sn=An+BnSn−1, n∈ℤ, and show that the distribution tail of its stationary solution has a power law decay.
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References
Akhmerov, R. R., Kamenskiĭ, M. I., Potapov, A. S., Rodkina, A. E. and Sadovskiĭ, B. N. (1992). Measures of Noncompactness and Condensing Operators. Birkhäuser, Basel.
Alsmeyer, G. (1997). The Markov renewal theorem and related results. Markov Process. Related Fields 3 103--127.
Asmussen, S. (1987). Applied Probability and Queues. Wiley, Chichester.
Athreya, K. B., McDonald, D. and Ney, P. A. (1978). Limit theorems for semi-Markov processes and renewal theory for Markov chains. Ann. Probab. 6 788--797.
Athreya, K. B. and Ney, P. A. (1978). A new approach to the limit theory of recurrent Markov chains. Trans. Amer. Math. Soc. 245 493--501.
Brandt, A. (1986). The stochastic equation $Y_n+1=A_nY_n+B_n$ with stationary coefficients. Adv. in Appl. Probab. 18 211--220.
de Saporta, B. (2005). Tail of the stationary solution of the stochastic equation $Y_ n+1=a_ nY_ n+b_ n$ with Markovian coefficients. Stochastic Process. Appl. 115 1954--1978.
Embrechts, P. and Goldie, C. M. (1994). Perpetuities and random equations. In Asymptotic Statistics (Prague, 1993) 75--86. Contrib. Statist. Physica, Heidelberg.
Goldie, C. M. (1991). Implicit renewal theory and tails of solutions of random equations. Ann. Appl. Probab. 1 126--166.
Goldie, C. M. and Grübel, R. (1996). Perpetuities with thin tails. Adv. in Appl. Probab. 28 463--480.
Grey, D. R. (1994). Regular variation in the tail behaviour of solutions of random difference equations. Ann. Appl. Probab. 4 169--183.
Grincevičjus, A. K. (1975). On a limit distribution for a random walk on the line. Lithuanian Math. J. 15 580--589.
Grincevičjus, A. K. (1980). Products of random affine transformations. Lithuanian Math. J. 20 279--282.
Kesten, H. (1973). Random difference equations and renewal theory for products of random matrices. Acta Math. 131 207--248.
Kesten, H. (1974). Renewal theory for functionals of a Markov chain with general state space. Ann. Probab. 2 355--386.
Mayer-Wolf, E., Roitershtein, A. and Zeitouni, O. (2004). Limit theorems for one-dimensional transient random walks in Markov environments. Ann. Inst. H. Poincaré Probab. Statist. 40 635--659.
Meyn, S. P. and Tweedie, R. L. (1993). Markov Chains and Stochastic Stability. Springer, London.
Nummelin, E. (1984). General Irreducible Markov Chains and Nonnegative Operators. Cambridge Univ. Press.
Nussbaum, R. D. (1981). Eigenvectors of nonlinear positive operators and the linear Krein--Rutman theorem. Fixed Point Theory. Lecture Notes in Math. 886 309--330. Springer, Berlin.
Rachev, S. T. and Samorodnitsky, G. (1995). Limit laws for a stochastic process and random recursion arising in probabilistic modelling. Adv. in Appl. Probab. 27 185--202.
Revuz, D. (1975). Markov Chains. North-Holland, Amsterdam.
Shurenkov, V. M. (1984). On Markov renewal theory. Teor. Veroyatnost. i Primenen. 29 248--263.
Vervaat, W. (1979). On a stochastic difference equation and a representation of nonnegative infinitely divisible random variables. Adv. in Appl. Probab. 11 750--783.
Yosida, K. and Kakutani, S. (1941). Operator-theoretical treatment of Markoff's process and mean ergodic theorem. Ann. of Math. (2) 42 188--228.