TY - JOUR
T1 - Small deviations of sums of correlated stationary gaussian sequences
AU - Aurzada, F.
AU - Lifshits, M. A.
PY - 2017/1/1
Y1 - 2017/1/1
N2 - We consider the small deviation probabilities (SDP) in the uniform norm for sums of stationary Gaussian sequences. For the cases of constant boundaries and boundaries tending to zero, we obtain quite general results. For the case of the boundaries tending to infinity, we focus our attention on the discrete analogues of the fractional Brownian motion (FBM). It turns out that the lower bounds for the SDP can be transferred from the well-studied FBM case to the discrete time setting under the usual assumptions that imply weak convergence, while the transfer of the corresponding upper bounds necessarily requires a deeper knowledge of the spectral structure of the underlying stationary sequence.
AB - We consider the small deviation probabilities (SDP) in the uniform norm for sums of stationary Gaussian sequences. For the cases of constant boundaries and boundaries tending to zero, we obtain quite general results. For the case of the boundaries tending to infinity, we focus our attention on the discrete analogues of the fractional Brownian motion (FBM). It turns out that the lower bounds for the SDP can be transferred from the well-studied FBM case to the discrete time setting under the usual assumptions that imply weak convergence, while the transfer of the corresponding upper bounds necessarily requires a deeper knowledge of the spectral structure of the underlying stationary sequence.
KW - Fractional brownian motion
KW - Fractional gaussian noise
KW - Gaussian process
KW - Small deviation probability
KW - Stationary gaussian sequence
UR - http://www.scopus.com/inward/record.url?scp=85039147622&partnerID=8YFLogxK
U2 - 10.1137/S0040585X97T988356
DO - 10.1137/S0040585X97T988356
M3 - Article
AN - SCOPUS:85039147622
VL - 61
SP - 540
EP - 568
JO - Theory of Probability and its Applications
JF - Theory of Probability and its Applications
SN - 0040-585X
IS - 4
ER -