arXiv subjects

George Deligiannidis

Publications and source records attributed to George Deligiannidis.

61 records · Page 4Linked to original sources

arXiv2016

Which ergodic averages have finite asymptotic variance?

We show that the class of $L^2$ functions for which ergodic averages of a reversible Markov chain have finite asymptotic variance is determined by the class of $L^2$ functions for which ergodic averages of its associated jump chain have finite asymptotic variance. This allows us to characterize completely which ergodic averages have finite asymptotic variance when the Markov chain is an independence sampler. In addition, we obtain a simple sufficient condition for all ergodic averages of $L^2$ functions of the primary variable in a pseudo-marginal Markov chain to have finite asymptotic variance.

stat.CO↗

arXiv2015

Optimal bounds for self-intersection local times

For a random walk $S_n, n\geq 0$ in $\mathbb{Z}^d$, let $l(n,x)$ be its local time at the site $x\in \mathbb{Z}^d$. Define the $α$-fold self intersection local time $L_n(α) := \sum_{x} l(n,x)^α$, and let $L_n(α|ε, d)$ the corresponding quantity for $d$-dimensional simple random walk. Without imposing any moment conditions, we show that the variances of the local times $\mathop{var}(L_n(α))$ of any genuinely $d$-dimensional random walk are bounded above by the corresponding characteristics of the simple symmetric random walk in $\mathbb{Z}^d$, i.e. $\mathop{var}(L_n(α)) \leq C \mathop{var}[L_n(α|ε, d)]\sim K_{d,α}v_{d,α}(n)$. In particular, variances of local times of all genuinely $d$-dimensional random walks, $d\geq 4$, are similar to the $4$-dimensional symmetric case $\mathop{var}(L_n(α)) = O(n)$. On the other hand, in dimensions $d\leq 3$ the resemblance to the simple random walk $\liminf_{n\to \infty} \mathop{var}(L_n(α))/v_{d,α}(n)>0$ implies that the jumps must have zero mean and finite second moment.

math.PR↗

arXiv2015

Relative Complexity of Random Walks in Random Scenery in the absence of a weak invariance principle for the local times

We answer the question of Aaronson about the relative complexity of Random Walks in Random Sceneries driven by either aperiodic two dimensional random walks, two-dimensional Simple Random walk, or by aperiodic random walks in the domain of attraction of the Cauchy distribution. A key step is proving that the range of the random walk satisfies the Fölner property almost surely.

math.PR↗

arXiv2014

Efficient implementation of Markov chain Monte Carlo when using an unbiased likelihood estimator

When an unbiased estimator of the likelihood is used within a Metropolis--Hastings chain, it is necessary to trade off the number of Monte Carlo samples used to construct this estimator against the asymptotic variances of averages computed under this chain. Many Monte Carlo samples will typically result in Metropolis--Hastings averages with lower asymptotic variances than the corresponding Metropolis--Hastings averages using fewer samples. However, the computing time required to construct the likelihood estimator increases with the number of Monte Carlo samples. Under the assumption that the distribution of the additive noise introduced by the log-likelihood estimator is Gaussian with variance inversely proportional to the number of Monte Carlo samples and independent of the parameter value at which it is evaluated, we provide guidelines on the number of samples to select. We demonstrate our results by considering a stochastic volatility model applied to stock index returns.

stat.ME↗

arXiv2014

Asymptotic variance of stationary reversible and normal Markov processes

We obtain necessary and sufficient conditions for the regular variation of the variance of partial sums of functionals of discrete and continuous-time stationary Markov processes with normal transition operators. We also construct a class of Metropolis-Hastings algorithms which satisfy a central limit theorem and invariance principle when the variance is not linear in $n$.

math.PR↗

arXiv2013

Variance of partial sums of stationary sequences

Let $X_1,X_2,\ldots$ be a centred sequence of weakly stationary random variables with spectral measure $F$ and partial sums $S_n=X_1+\cdots+X_n$. We show that $\operatorname {var}(S_n)$ is regularly varying of index $γ$ at infinity, if and only if $G(x):=\int_{-x}^xF(\mathrm {d}x)$ is regularly varying of index $2-γ$ at the origin ($0<γ<2$).

math.PR↗

arXiv2010

An asymptotic variance of the self-intersections of random walks

We present a Darboux-Wiener type lemma and apply it to obtain an exact asymptotic for the variance of the self-intersection of one and two-dimensional random walks. As a corollary, we obtain a central limit theorem for random walk in random scenery conjectured by Kesten and Spitzer in 1979.

math.PR↗