Search Results - "Stoev, Stilian"

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  1. 1

    Inference for Monotone Functions Under Short- and Long-Range Dependence: Confidence Intervals and New Universal Limits by Bagchi, Pramita, Banerjee, Moulinath, Stoev, Stilian A.

    “…We introduce new point-wise confidence interval estimates for monotone functions observed with additive, dependent noise. Our methodology applies to both…”
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  2. 2

    AMON: An Open Source Architecture for Online Monitoring, Statistical Analysis, and Forensics of Multi-Gigabit Streams by Kallitsis, Michael, Stoev, Stilian A., Bhattacharya, Shrijita, Michailidis, George

    “…The Internet, as a global system of interconnected networks, carries an extensive array of information resources and services. Key requirements include good…”
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  3. 3

    Inference for dynamic and latent variable models via iterated, perturbed Bayes maps by Ionides, Edward L., Nguyen, Dao, Atchadé, Yves, Stoev, Stilian, King, Aaron A.

    “…Iterated filtering algorithms are stochastic optimization procedures for latent variable models that recursively combine parameter perturbations with latent…”
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  4. 4

    On the rate of concentration of maxima in Gaussian arrays by Kartsioukas, Rafail, Gao, Zheng, Stoev, Stilian

    Published in Extremes (Boston) (01-03-2021)
    “…Recently in Gao and Stoev ( 2020 ) it was established that the concentration of maxima phenomenon is the key to solving the exact sparse support recovery…”
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  5. 5

    ERGODIC PROPERTIES OF SUM- AND MAX-STABLE STATIONARY RANDOM FIELDS VIA NULL AND POSITIVE GROUP ACTIONS by Wang, Yizao, Roy, Parthanil, Stoev, Stilian A.

    Published in The Annals of probability (01-01-2013)
    “…We establish characterization results for the ergodicity of stationary symmetric α-stable (SαS) and α-Fréchet random fields. We show that the result of…”
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  6. 6

    On the ergodicity and mixing of max-stable processes by Stoev, Stilian A.

    “…Max-stable processes arise in the limit of component-wise maxima of independent processes, under appropriate centering and normalization. In this paper, we…”
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  7. 7

    Conditional sampling for spectrally discrete max-stable random fields by Wang, Yizao, Stoev, Stilian A.

    Published in Advances in applied probability (01-06-2011)
    “…Max-stable random fields play a central role in modeling extreme value phenomena. We obtain an explicit formula for the conditional probability in general…”
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  8. 8

    On the structure and representations of max-stable processes by Wang, Yizao, Stoev, Stilian A.

    Published in Advances in applied probability (01-09-2010)
    “…We develop classification results for max-stable processes, based on their spectral representations. The structure of max-linear isometries and minimal…”
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  9. 9

    On the association of sum- and max-stable processes by Wang, Yizao, Stoev, Stilian A.

    Published in Statistics & probability letters (01-03-2010)
    “…We address the notion of association of sum- and max-stable processes from the perspective of linear and max-linear isometries. We establish the appealing…”
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  10. 10

    Estimating Heavy-Tail Exponents Through Max Self-Similarity by Stoev, S A, Michailidis, G, Taqqu, M S

    Published in IEEE transactions on information theory (01-03-2011)
    “…In this paper, a novel approach to the problem of estimating the heavy-tail exponent α >; 0 of a distribution is proposed. It is based on the fact that…”
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  11. 11

    How rich is the class of multifractional Brownian motions? by Stoev, Stilian A., Taqqu, Murad S.

    “…The multifractional Brownian motion (MBM) processes are locally self-similar Gaussian processes. They extend the classical fractional Brownian motion processes…”
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  12. 12

    Fast Algorithms for Optimal Link Selection in Large-Scale Network Monitoring by Kallitsis, M. G., Stoev, S. A., Michailidis, G.

    Published in IEEE transactions on signal processing (01-04-2013)
    “…The robustness and integrity of IP networks require efficient tools for traffic monitoring and analysis, which scale well with traffic volume and network size…”
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  13. 13

    Extreme value theory with operator norming by Meerschaert, Mark M., Scheffler, Hans-Peter, Stoev, Stilian A.

    Published in Extremes (Boston) (01-12-2013)
    “…A new approach to extreme value theory is presented for vector data with heavy tails. The tail index is allowed to vary with direction, where the directions…”
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  14. 14

    On the estimation of the heavy-tail exponent in time series using the max-spectrum by Stoev, Stilian A., Michailidis, George

    “…This paper addresses the problem of estimating the tail index α of distributions with heavy, Pareto‐type tails for dependent data, that is of interest in the…”
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  15. 15

    Extremal limit theorems for observations separated by random power law waiting times by Meerschaert, Mark M., Stoev, Stilian A.

    “…This paper develops extreme value theory for random observations separated by random waiting times whose exceedence probability falls off like a power law. In…”
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  16. 16

    Stochastic properties of the linear multifractional stable motion by Stoev, Stilian, Taqqu, Murad S.

    Published in Advances in applied probability (01-12-2004)
    “…We study a family of locally self-similar stochastic processes Y = {Y(t)} t∈ℝ with α-stable distributions, called linear multifractional stable motions. They…”
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  17. 17

    Stochastic integral representations and classification of sum- and max-infinitely divisible processes by KABLUCHKO, ZAKHAR, STOEV, STILIAN

    “…Introduced is the notion of minimality for spectral representations of sum- and max-infinitely divisible processes and it is shown that the minimal spectral…”
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  18. 18

    Exchangeable random partitions from max-infinitely-divisible distributions by Stoev, Stilian, Wang, Yizao

    Published in Statistics & probability letters (01-03-2019)
    “…The hitting partitions are random partitions that arise from the investigation of so-called hitting scenarios of max-infinitely-divisible…”
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  19. 19

    Probabilities of Concurrent Extremes by Dombry, Clément, Ribatet, Mathieu, Stoev, Stilian

    “…The statistical modeling of spatial extremes has been an active area of recent research with a growing domain of applications. Much of the existing…”
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