21 notizie
Contents: James Burridge , Richard Cowan , Isaac Ma . Full- and half-Gilbert tessellations with rectangular cells . 1--19. C. Hirsch , D. Neuhäuser , V. Schmidt . Connectivity of random geometric graphs related to minimal spanning forests . 20--36. Jinghai Shao , Xiuping Wang . . 37--50. K. D. Glazebrook , D. J. Hodge , C. Kirkbride . Monotone policies and indexability for bidirectional restless bandits . 51--85. E. H. A. Dia . Error bounds for small jumps of Lvy processes . 86--105. Predrag R. Jelenković , Jian Tan . Characterizing heavy-tailed distributions induced by retransmissions . 106--138. Bikramjit Das , Abhimanyu Mitra , Sidney Resnick . Living on the multidimensional edge: seeking hidden risks using regular variation . 139--163. Pavel V. Gapeev , Albert N. Shiryaev . Bayesian quickest detection problems for some diffusion processes . 164--185. Sidney I. Resnick , David Zeber . Asymptotics of Markov kernels and the tail chain . 186--213. Nikolaos Limnios , Anatoliy Swishchuk . Discrete-Time Semi-Markov Random Evolutions and their Applications . 214--240. Fenglong Guo , Dingcheng Wang . Finite- and infinite-time ruin probabilities with general stochastic investment return processes and bivariate upper tail independent and heavy-tailed claims . 241--273. F. Avram , A. J. E. M. Janssen , J. S. H. Van Leeuwaarden . Loss systems with slow retrials in the Halfin–Whitt regime . 274--294.
Contents: ERY ARIAS-CASTRO , BRUNO PELLETIER , PIERRE PUDLO . The normalized graph cut and Cheeger constant: from discrete to continuous . 907--937. M. Reitzner , E. Spodarev , D. Zaporozhets . Set reconstruction by Voronoi cells . 938--953. M. Riplinger , M. Spiess . Asymptotic properties of the approximate inverse estimator for directional distributions . 954--976. Joaquin Fontbona , Hélène Guérin , Florent Malrieu . Quantitative estimates for the long-time behavior of an ergodic variant of the telegraph process . 977--994. Souvik Ghosh , Soumyadip Ghosh . A strong law for the rate of growth of long latency periods in a cloud computing service . 995--1017. ALESSANDRO ANDREOLI , FRANCESCO CARAVENNA , PAOLO DAI PRA , GUSTAVO POSTA . Scaling and multiscaling in financial series: a simple model . 1018--1051. Michael Kelly . A hierarchical probability model of colon cancer . 1052--1083. Christoph Czichowsky , Martin Schweizer . Convex duality in mean-variance hedging under convex trading constraints . 1084--1112. RAFAŁ KULIK , PHILIPPE SOULIER . Limit theorems for long-memory stochastic volatility models with infinite variance: partial sums and sample covariances . 1113--1141. MARIANA OLVERA-CRAVIOTO . Asymptotics for weighted random sums . 1142--1172. HOCK PENG CHAN , SHAOJIE DENG , TZE-LEUNG LAI . Rare-event simulation of heavy-tailed random walks by sequential importance sampling and resampling . 1173--1196.
24 notizie
Advances in Theoretical and Mathematical Physics, Volume 16, Number 1 (2012)
Contents: Junya Yagi . Chiral algebras of (0, 2) models . 1--37. Marco Castrillón López , Jamie Muñoz Masqué . Hamiltonian structure of gauge-invariant variational problems . 39--63. Vladimir V. Bazhanov , Sergey M. Sergeev . A master solution of the quantum Yang–Baxter equation and classical discrete integrable equations . 65--95. Axel Kleinschmidt , Hermann Nicolai , Jakob Palmkvist . Modular realizations of hyperbolic Weyl groups . 97--148. Domenico Fiorenza , Urs Schreiber , Jim Stasheff . Čech cocycles for differential characteristic classes: an ∞-Lie theoretic construction . 149--250. Jock McOrist , Ilarion V. Melnikov . Old issues and linear sigma models . 251--288. Jennifer Maier , Thomas Nikolaus , Christoph Schweigert . Equivariant modular categories via Dijkgraaf–Witten theory . 289--358.
matematica | advances in theoretical and mathematical physics
Advances in Theoretical and Mathematical Physics, Volume 16, Number 2 (2012)
Contents: Todd A. Oliynyk . The fast Newtonian limit for perfect fluids . 359--391. Joachim Schröter . An extension of Friedmann–Robertson–Walker theory beyond big bang . 393--419. Min–xin Huang . Higher genus BMN correlators: factorization and recursion relations . 421--503. Giuseppe De Nittis , Giovanni Landi . Generalized TKNN-equations . 505--547. Gianluca Calcagni . Geometry of fractional spaces . 549--644. Fabio Ciolli , Giuseppe Ruzzi , Ezio Vasselli . Causal posets, loops and the construction of nets of local algebras for QFT . 645--691. Norbert Riedel . Persistence of gaps in the spectrum of certain almost periodic operators . 693--712. Indranil Biswas , Matthias Stemmler . Vortex equation and reflexive sheaves . 713--723.
matematica | advances in theoretical and mathematical physics
2197 notizie
Publication date: Available online 22 May 2013 Source: Advances in Water Resources Author(s): Chunhui Lu , Adrian D. Werner Quantifying the timescales associated with moving freshwater-seawater interfaces is critical for effective management of coastal groundwater resources. In this study, timescales of interface movement in response to both inland and coastal water level variations are investigated. We first assume that seawater intrusion (SWI) and retreat (SWR) are driven by an instantaneous freshwater-level variation at the inland boundary. Numerical modelling results reveal that logarithmic timescales of SWI (lnTi ) and SWR (lnTr ) can be described respectively by various simple linear equations. For example, SWI timescales are described by lnTi = a +blnh’f-s , where a and b are linear regression coefficients and h’f-s is the boundary head difference after an instantaneous drop of inland freshwater head. For SWR cases with the same initial conditions, but with different increases in freshwater head, lnTr = c +dΔXT , where c and d are regression coefficients and ΔXT is the distance of toe response that can be estimated by a steady-state, sharp-interface analytical solution. For SWR cases with the same freshwater head increase, but with different initial conditions, in contrast, lnTr = e + flnΔXT , where e and f are regression coefficients. The timescale of toe response caused by an instantaneous variation of sea level is almost equivalent to that induced by an instantaneous inland head variation with the same magnitude of water level change, but opposite in direction. Accordingly, the empirical equations of this study are also applicable for sea-level variations in head-controlled systems or for simultaneous variations of both inland and coastal water levels. Despite the idealized conceptual models adopted in this study, the results imply that for a particular coastal aquifer, SWI timescales are controlled by the boundary water levels after variations, whereas SWR timescales are dominated by the distance of toe response.
Mixture Model Based Multivariate Statistical Analysis of Multiply Censored Environmental Data
Publication date: Available online 16 May 2013 Source: Advances in Water Resources Author(s): Jianxun He Environmental data are commonly constrained by a detection limit (DL) because of the restriction of experimental apparatus. In particular due to the changes of experimental units or assay methods, the observed data are often cut off by more than one DL. Measurements below the DLs are typically replaced by an arbitrary value such as zeros, half of DLs, or DLs for convenience of analysis. However, this method is widely considered unreliable and prone to bias. In contrast, maximum likelihood estimation (MLE) method for censored data has been developed for better performance and statistical justification. However, the existing MLE methods seldom address the multivariate context of censored environmental data especially for water quality. This paper proposes using a mixture model to flexibly approximate the underlying distribution of the observed data due to its good approximation capability and generation mechanism. In particular, Gaussian mixture model (GMM) is mainly focused in this study. To cope with the censored data with multiple DLs, an expectation-maximization (EM) algorithm in a multivariate setting is developed. The proposed statistical analysis approach is verified from both the simulated data and real water quality data.
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