English

A Local Limit Theorem for the Minimum of a Random Walk with Markovian Increasements

Probability 2017-12-05 v2

Abstract

Let (Ω,F,P)(\Omega,\mathcal{F}, \mathbb{P}) be a probability space and EE be a finite set. Assume that X=(Xn)X=(X_n) is an irreducible and aperiodic Markov chain, defined on (Ω,F,P)(\Omega,\mathcal{F}, \mathbb{P}), with values in EE and with transition probability P=(pi,j)i,jP=\Big(p_{i,j}\Big)_{i,j}. Let (F(i,j,\dx))i,jE(F(i,j,\d x))_{i,j\in E} be a family of probability measures on R\mathbb{R}. Consider a semi-markovian chain (Yn,Xn)(Y_n,X_n) on R×E\mathbb{R}\times E with transition probability P~\widetilde{P}, defined by P~((u,i),A×{j})=P(Yn+1A,Xn+1=jYn=u,Xn=i)=pi,jF(i,j,A)\widetilde{P}\Big((u,i),A\times\{j\}\Big)=\mathbb{P}(Y_{n+1}\in A,X_{n+1}=j|Y_n= u,X_n=i)=p_{i,j}F(i,j,A), for any (u,i)R×E(u,i)\in\mathbb{R}\times E, any Borel set ARA\subset\mathbb{R} and any jEj\in E. We study the asymptotic behavior of the sequence of Laplace transforms of (Xn,mn)(X_n,m_n), where mn=min(S0,S1,...,Sn)m_n=\min(S_0,S_1,...,S_n) and Sn=Y0+...+Yn1S_n=Y_0+...+Y_{n-1}. Under quite general assumptions on F(i,j,dx)F(i,j,dx), we prove that for all (i,j)E×E(i,j)\in E\times E, n\Ei[exp(λmn),Xn=j]\sqrt{n}\E_i[\exp(\lambda m_n), X_n=j] converges to a positive function Hi,j(λ)H_{i,j}(\lambda) and we obtain further informations on this limit function as λ0+\lambda\to 0^+.

Keywords

Cite

@article{arxiv.1104.1554,
  title  = {A Local Limit Theorem for the Minimum of a Random Walk with Markovian Increasements},
  author = {Yinna Ye},
  journal= {arXiv preprint arXiv:1104.1554},
  year   = {2017}
}

Comments

40 pages, 3 figures; updated author's present address, corrected typos, unified notations