Latest articles of Modern Stochastics: Theory and Applications
http://www.vmsta.org/journal/VMSTA/feeds/latest
https://www.vmsta.org/https://www.vmsta.org/Latest articles of Modern Stochastics: Theory and Applications
http://www.vmsta.org/journal/VMSTA/feeds/latest
enThu, 28 Oct 2021 10:33:16 +0300<![CDATA[Bounded in the mean solutions of a second-order difference equation]]>
https://www.vmsta.org/journal/VMSTA/article/220
https://www.vmsta.org/journal/VMSTA/article/220Sufficient conditions are given for the existence of a unique bounded in the mean solution to a second-order difference equation with jumps of operator coefficients in a Banach space. The question of the proximity of this solution to the stationary solution of the corresponding difference equation with constant operator coefficients is studied. PDFXML]]>Sufficient conditions are given for the existence of a unique bounded in the mean solution to a second-order difference equation with jumps of operator coefficients in a Banach space. The question of the proximity of this solution to the stationary solution of the corresponding difference equation with constant operator coefficients is studied. PDFXML]]>Mykhailo Horodnii,Victoriia KravetsThu, 09 Sep 2021 00:00:00 +0300<![CDATA[Bias reduction of a conditional maximum likelihood estimator for a Gaussian second-order moving average model]]>
https://www.vmsta.org/journal/VMSTA/article/218
https://www.vmsta.org/journal/VMSTA/article/218In this study, we consider a bias reduction of the conditional maximum likelihood estimators for the unknown parameters of a Gaussian second-order moving average (MA(2)) model. In many cases, we use the maximum likelihood estimator because the estimator is consistent. However, when the sample size n is small, the error is large because it has a bias of $O({n^{-1}})$. Furthermore, the exact form of the maximum likelihood estimator for moving average models is slightly complicated even for Gaussian models. We sometimes rely on simpler maximum likelihood estimation methods. As one of the methods, we focus on the conditional maximum likelihood estimator and examine the bias of the conditional maximum likelihood estimator for a Gaussian MA(2) model. Moreover, we propose new estimators for the unknown parameters of the Gaussian MA(2) model based on the bias of the conditional maximum likelihood estimators. By performing simulations, we investigate properties of this bias, as well as the asymptotic variance of the conditional maximum likelihood estimators for the unknown parameters. Finally, we confirm the validity of the new estimators through this simulation study. PDFXML]]>In this study, we consider a bias reduction of the conditional maximum likelihood estimators for the unknown parameters of a Gaussian second-order moving average (MA(2)) model. In many cases, we use the maximum likelihood estimator because the estimator is consistent. However, when the sample size n is small, the error is large because it has a bias of $O({n^{-1}})$. Furthermore, the exact form of the maximum likelihood estimator for moving average models is slightly complicated even for Gaussian models. We sometimes rely on simpler maximum likelihood estimation methods. As one of the methods, we focus on the conditional maximum likelihood estimator and examine the bias of the conditional maximum likelihood estimator for a Gaussian MA(2) model. Moreover, we propose new estimators for the unknown parameters of the Gaussian MA(2) model based on the bias of the conditional maximum likelihood estimators. By performing simulations, we investigate properties of this bias, as well as the asymptotic variance of the conditional maximum likelihood estimators for the unknown parameters. Finally, we confirm the validity of the new estimators through this simulation study. PDFXML]]>Fumiaki Honda,Takeshi KurosawaWed, 04 Aug 2021 00:00:00 +0300<![CDATA[Probabilistic analysis of vantage point trees]]>
https://www.vmsta.org/journal/VMSTA/article/219
https://www.vmsta.org/journal/VMSTA/article/219Probabilistic properties of vantage point trees are studied. A vp-tree built from a sequence of independent identically distributed points in ${[-1,\hspace{0.1667em}1]^{d}}$ with the ${\ell _{\infty }}$-distance function is considered. The length of the leftmost path in the tree, as well as partitions over the space it produces are analyzed. The results include several convergence theorems regarding these characteristics, as the number of nodes in the tree tends to infinity. PDFXML]]>Probabilistic properties of vantage point trees are studied. A vp-tree built from a sequence of independent identically distributed points in ${[-1,\hspace{0.1667em}1]^{d}}$ with the ${\ell _{\infty }}$-distance function is considered. The length of the leftmost path in the tree, as well as partitions over the space it produces are analyzed. The results include several convergence theorems regarding these characteristics, as the number of nodes in the tree tends to infinity. PDFXML]]>Vladyslav BohunWed, 04 Aug 2021 00:00:00 +0300<![CDATA[Convexity and robustness of the Rényi entropy]]>
https://www.vmsta.org/journal/VMSTA/article/216
https://www.vmsta.org/journal/VMSTA/article/216We study convexity properties of the Rényi entropy as function of $\alpha >0$ on finite alphabets. We also describe robustness of the Rényi entropy on finite alphabets, and it turns out that the rate of respective convergence depends on initial alphabet. We establish convergence of the disturbed entropy when the initial distribution is uniform but the number of events increases to ∞ and prove that the limit of Rényi entropy of the binomial distribution is equal to Rényi entropy of the Poisson distribution. PDFXML]]>We study convexity properties of the Rényi entropy as function of $\alpha >0$ on finite alphabets. We also describe robustness of the Rényi entropy on finite alphabets, and it turns out that the rate of respective convergence depends on initial alphabet. We establish convergence of the disturbed entropy when the initial distribution is uniform but the number of events increases to ∞ and prove that the limit of Rényi entropy of the binomial distribution is equal to Rényi entropy of the Poisson distribution. PDFXML]]>Filipp Buryak,Yuliya MishuraMon, 26 Jul 2021 00:00:00 +0300<![CDATA[Estimation in a linear errors-in-variables model under a mixture of classical and Berkson errors]]>
https://www.vmsta.org/journal/VMSTA/article/217
https://www.vmsta.org/journal/VMSTA/article/217A linear structural regression model is studied, where the covariate is observed with a mixture of the classical and Berkson measurement errors. Both variances of the classical and Berkson errors are assumed known. Without normality assumptions, consistent estimators of model parameters are constructed and conditions for their asymptotic normality are given. The estimators are divided into two asymptotically independent groups. PDFXML]]>A linear structural regression model is studied, where the covariate is observed with a mixture of the classical and Berkson measurement errors. Both variances of the classical and Berkson errors are assumed known. Without normality assumptions, consistent estimators of model parameters are constructed and conditions for their asymptotic normality are given. The estimators are divided into two asymptotically independent groups. PDFXML]]>Mykyta Yakovliev,Alexander KukushMon, 26 Jul 2021 00:00:00 +0300<![CDATA[Editorial]]>
https://www.vmsta.org/journal/VMSTA/article/215
https://www.vmsta.org/journal/VMSTA/article/215PDF XML]]>PDF XML]]>Mark PodolskijWed, 23 Jun 2021 00:00:00 +0300<![CDATA[Second order elliptic partial differential equations driven by Lévy white noise]]>
https://www.vmsta.org/journal/VMSTA/article/212
https://www.vmsta.org/journal/VMSTA/article/212This paper deals with linear stochastic partial differential equations with variable coefficients driven by Lévy white noise. First, an existence theorem for integral transforms of Lévy white noise is derived and the existence of generalized and mild solutions of second order elliptic partial differential equations is proved. Further, the generalized electric Schrödinger operator for different potential functions V is discussed. PDFXML]]>This paper deals with linear stochastic partial differential equations with variable coefficients driven by Lévy white noise. First, an existence theorem for integral transforms of Lévy white noise is derived and the existence of generalized and mild solutions of second order elliptic partial differential equations is proved. Further, the generalized electric Schrödinger operator for different potential functions V is discussed. PDFXML]]>David Berger,Farid MohamedTue, 22 Jun 2021 00:00:00 +0300<![CDATA[Sharp asymptotics for q-norms of random vectors in high-dimensional ℓpn-balls]]>
https://www.vmsta.org/journal/VMSTA/article/213
https://www.vmsta.org/journal/VMSTA/article/213Sharp large deviation results of Bahadur–Ranga Rao type are provided for the q-norm of random vectors distributed on the ${\ell _{p}^{n}}$-ball ${\mathbb{B}_{p}^{n}}$ according to the cone probability measure or the uniform distribution for $1\le q<p<\infty $, thereby furthering previous large deviation results by Kabluchko, Prochno and Thäle in the same setting. These results are then applied to deduce sharp asymptotics for intersection volumes of different ${\ell _{p}^{n}}$-balls in the spirit of Schechtman and Schmuckenschläger, and for the length of the projection of an ${\ell _{p}^{n}}$-ball onto a line with uniform random direction. The sharp large deviation results are proven by providing convenient probabilistic representations of the q-norms, employing local limit theorems to approximate their densities, and then using geometric results for asymptotic expansions of Laplace integrals to integrate these densities and derive concrete probability estimates. PDFXML]]>Sharp large deviation results of Bahadur–Ranga Rao type are provided for the q-norm of random vectors distributed on the ${\ell _{p}^{n}}$-ball ${\mathbb{B}_{p}^{n}}$ according to the cone probability measure or the uniform distribution for $1\le q<p<\infty $, thereby furthering previous large deviation results by Kabluchko, Prochno and Thäle in the same setting. These results are then applied to deduce sharp asymptotics for intersection volumes of different ${\ell _{p}^{n}}$-balls in the spirit of Schechtman and Schmuckenschläger, and for the length of the projection of an ${\ell _{p}^{n}}$-ball onto a line with uniform random direction. The sharp large deviation results are proven by providing convenient probabilistic representations of the q-norms, employing local limit theorems to approximate their densities, and then using geometric results for asymptotic expansions of Laplace integrals to integrate these densities and derive concrete probability estimates. PDFXML]]>Tom KaufmannTue, 22 Jun 2021 00:00:00 +0300<![CDATA[Malliavin–Stein method: a survey of some recent developments]]>
https://www.vmsta.org/journal/VMSTA/article/214
https://www.vmsta.org/journal/VMSTA/article/214Initiated around the year 2007, the Malliavin–Stein approach to probabilistic approximations combines Stein’s method with infinite-dimensional integration by parts formulae based on the use of Malliavin-type operators. In the last decade, Malliavin–Stein techniques have allowed researchers to establish new quantitative limit theorems in a variety of domains of theoretical and applied stochastic analysis. The aim of this survey is to illustrate some of the latest developments of the Malliavin–Stein method, with specific emphasis on extensions and generalizations in the framework of Markov semigroups and of random point measures. PDFXML]]>Initiated around the year 2007, the Malliavin–Stein approach to probabilistic approximations combines Stein’s method with infinite-dimensional integration by parts formulae based on the use of Malliavin-type operators. In the last decade, Malliavin–Stein techniques have allowed researchers to establish new quantitative limit theorems in a variety of domains of theoretical and applied stochastic analysis. The aim of this survey is to illustrate some of the latest developments of the Malliavin–Stein method, with specific emphasis on extensions and generalizations in the framework of Markov semigroups and of random point measures. PDFXML]]>Ehsan Azmoodeh,Giovanni Peccati,Xiaochuan YangTue, 22 Jun 2021 00:00:00 +0300<![CDATA[Optimal transport between determinantal point processes and application to fast simulation]]>
https://www.vmsta.org/journal/VMSTA/article/211
https://www.vmsta.org/journal/VMSTA/article/211Two optimal transport problems between determinantal point processes (DPP for short) are investigated. It is shown how to estimate the Kantorovitch–Rubinstein and Wasserstein-2 distances between distributions of DPP. These results are applied to evaluate the accuracy of a fast but approximate simulation algorithm of the Ginibre point process restricted to a circle. One can now simulate in a reasonable amount of time more than ten thousands points. PDFXML]]>Two optimal transport problems between determinantal point processes (DPP for short) are investigated. It is shown how to estimate the Kantorovitch–Rubinstein and Wasserstein-2 distances between distributions of DPP. These results are applied to evaluate the accuracy of a fast but approximate simulation algorithm of the Ginibre point process restricted to a circle. One can now simulate in a reasonable amount of time more than ten thousands points. PDFXML]]>Laurent Decreusefond,Guillaume MorozWed, 02 Jun 2021 00:00:00 +0300