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Discussion of "Feature Matching in Time Series Modeling" by Y. Xia and H. Tong [arXiv:1104.3073]

Methodology · Statistics 2012-01-09 Edward L. Ionides

Discussion of "Feature Matching in Time Series Modeling" by Y. Xia and H. Tong [arXiv:1104.3073]

Methodology · Statistics 2012-01-09 Kung-Sik Chan , Ruey S. Tsay

Discussion of "Feature Matching in Time Series Modeling" by Y. Xia and H. Tong [arXiv:1104.3073]

Methodology · Statistics 2012-01-09 Bruce E. Hansen

It is shown that the variable bandwidth density estimator proposed by McKay (1993a and b) following earlier findings by Abramson (1982) approximates density functions in $C^4(\mathbb R^d)$ at the minimax rate in the supremum norm over…

Statistics Theory · Mathematics 2013-05-07 Evarist Giné , Hailin Sang

We introduce a concept for random tilings which, comprising the conventional one, is also applicable to tiling ensembles without height representation. In particular, we focus on the random tiling entropy as a function of the tile…

Statistical Mechanics · Physics 2008-08-28 Christoph Richard , Moritz Hoeffe , Joachim Hermisson , Michael Baake

Rejoinder to "Statistical Modeling of Spatial Extremes" by A. C. Davison, S. A. Padoan and M. Ribatet [arXiv:1208.3378].

Methodology · Statistics 2012-08-20 A. C. Davison , S. A. Padoan , M. Ribatet

The analysis of experimental data with mixed-effects models requires decisions about the specification of the appropriate random-effects structure. Recently, Barr, Levy, Scheepers, and Tily, 2013 recommended fitting `maximal' models with…

Methodology · Statistics 2018-05-29 Douglas Bates , Reinhold Kliegl , Shravan Vasishth , Harald Baayen

Reply to a comment by T. Rakovszky, F. Pollmann, and C. W von Keyserlingk [arXiv:2010.07969].

Strongly Correlated Electrons · Physics 2021-06-16 Marko Znidaric

Comment on recent paper by I. Horv\'ath and P. Marko\v{s}, "Super-universality in Anderson localization", Phys. Rev. Lett. 129, 106601 (2022) [arXiv:2110.11266].

Disordered Systems and Neural Networks · Physics 2023-09-27 I. S. Burmistrov

We employ optimal control theory to study the problem of estimating the probability density function from a data set originating from an unknown probability distribution. The original variational problem is reformulated as a multi-stage…

Optimization and Control · Mathematics 2025-10-02 Markus Hegland , C. Yalçın Kaya

The super-parametric density estimators and its related algorism were suggested by Y. -S. Tsai et al [7]. The number of parameters is unlimited in the super- parametric estimators and it is a general theory in sense of unifying or…

Computation · Statistics 2008-11-07 Yeong-Shyeong Tsai , Ying-Lin Hsu , Mung-Chung Shung

This is a remark on a recent post by P. Denton, S. Parke, T. Tao, X. Zhang, Eigenvectors from eigenvalues, arXiv:1908.03795v1

Rings and Algebras · Mathematics 2019-11-21 Carlos Tomei

A recent letter titled "Explicit Analytical Solution for Random Close Packing in d=2 and d=3" published in Physical Review Letters proposes a first-principle computation of the random close packing (RCP) density in spatial dimensions d=2…

Statistical Mechanics · Physics 2025-09-01 Patrick Charbonneau , Peter K. Morse

We investigate different randomizations for mirror descent method. We try to propose such a randomization that allows us to use sparsity of the problem as much as it possible. In the paper one can also find a generalization of randomizaed…

Optimization and Control · Mathematics 2016-12-12 Anton Anikin , Alexander Gasnikov , Alexander Gornov

Classical designs of randomized experiments, going back to Fisher and Neyman in the 1930s still dominate practice even in online experimentation. However, such designs are of limited value for answering standard questions in settings,…

This is a comment on [G. Knight and R. Klages, Phys. Rev. E 84, 041135 (2011); also available at arXiv:1107.5293v2 [math-ph]].

Statistical Mechanics · Physics 2011-11-29 Thomas Gilbert , David P. Sanders

The paper comments on "Quantifying long-term scientific impact". It indicates that there is a mistake of [D. S. Wang , C. Song, A. L. Barabasi, Quantifying long-term scientific impact, Science 342, 127 (2013), arXiv:1306.3293].

Digital Libraries · Computer Science 2014-05-16 Jin-Li Guo , Qi Suo

This is a reply to the comment by Gilbert and Sanders [arXiv:1111.6271 (2011)]. We point out that their comment is a follow-up of a previous discussion which we briefly summarize before we refute their new criticism.

Mathematical Physics · Physics 2011-12-20 Rainer Klages , Georgie Knight

In the present paper we introduce new optimization algorithms for the task of density ratio estimation. More precisely, we consider extending the well-known KMM method using the construction of a suitable loss function, in order to…

Machine Learning · Computer Science 2023-09-15 Cristian Daniel Alecsa