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  2. Uniform limit theorems for wavelet density estimators

    https://www.statslab.cam.ac.uk/~nickl/Site/__files/AOP447.pdf
    22 Jul 2009: Donsker classes F. Our proofs will in fact show ‖P Wn Pn‖F = oP (1/.
  3. Adaptive estimation of a distribution function and its density in…

    https://www.statslab.cam.ac.uk/~nickl/Site/__files/BEJ239.pdf
    19 Nov 2010: Proof. Given ε > 0, apply Proposition 4 below with λ = ε so that ‖F Sn Fn‖ = oP (1/.
  4. Probab. Theory Relat. Fields (2008) 141:333–387DOI…

    https://www.statslab.cam.ac.uk/~nickl/Site/__files/ptrf08.pdf
    11 Sep 2008: n sup. f F. f (x)pn(x)d x. f (x)p0(x)d x. = OP(1), (3). ... supf F. |(Pn P)(µ̄n f f )| = oP(1/. n). The last two estimates prove (9) since F is P-Donsker.
  5. Global uniform risk bounds for wavelet deconvolution estimators

    https://www.statslab.cam.ac.uk/~nickl/Site/__files/AOS836.pdf
    17 Feb 2011: The Annals of Statistics2011, Vol. 39, No. 1, 201–231DOI: 10.1214/10-AOS836 Institute of Mathematical Statistics, 2011. GLOBAL UNIFORM RISK BOUNDS FOR WAVELETDECONVOLUTION ESTIMATORS. BY KARIM LOUNICI AND RICHARD NICKL. University of Cambridge. We
  6. State space collapse and diffusion approximation for a network…

    https://www.statslab.cam.ac.uk/~frank/PAPERS/AAP591.pdf
    30 Nov 2011: The Annals of Applied Probability2009, Vol. 19, No. 5, 1719–1780DOI: 10.1214/08-AAP591 Institute of Mathematical Statistics, 2009. STATE SPACE COLLAPSE AND DIFFUSION APPROXIMATIONFOR A NETWORK OPERATING UNDER A FAIR BANDWIDTH. SHARING POLICY. BY
  7. The Move-to-Front Rule for Multiple Lists

    https://www.statslab.cam.ac.uk/~rrw1/publications/Courcoubetis%20-%20Weber%201990%20The%20move-to-front%20rule%20for%20multiple%20lists.pdf
    15 Sep 2011: However,in the following section we discuss variations of the problem in which the op-timal policy does indeed lie within the class of partition policies.
  8. Mathematical Foundations of Infinite-Dimensional Statistical Models

    https://www.statslab.cam.ac.uk/~nickl/Site/__files/FULLPDF.pdf
    25 Feb 2020: Mathematical Foundations of Infinite-DimensionalStatistical Models. In nonparametric and high-dimensional statistical models, the classical Gauss–Fisher–Le Cam theory of the optimality of maximum likelihood and Bayesianposterior inference does
  9. 1034 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. ...

    https://www.statslab.cam.ac.uk/~rrw1/publications/Courcoubetis%20-%20Weber%202006%20%20Incentives%20for%20large%20peer-to-peer%20systems.pdf
    15 Sep 2011: Appendix I contains a derivation of the op-timization problem of maximizing expected social welfare,and Appendix II justifies the fact that it can be solve usingLagrangian methods. ... APPENDIX IIJUSTIFICATION FOR USE OF LAGRANGIAN METHODS. We prove that
  10. arXiv:math.PR/0001057 v1 11 Jan 2000

    https://www.statslab.cam.ac.uk/~grg/teaching/doyle.pdf
    14 Dec 2005: arX. iv:m. ath. PR/0. 0010. 57 v. 1 1. 1 Ja. n 20. 00! " # $ % & ' ( ) , -. & /. " 0 ) ) ). 1 % 2 0 " $ 3 4 5 6 1 7 8 9 9 9 ) ) ) :! 5! " ; ( < % 0 =! & > - (? / " $! @ &! = =<! " $ A! > B " % C D % " E 6 # 7. 1 % 2 0 " $ 3 4 5 6 1 7 8 9 F G H 4! I.
  11. climb.dvi

    https://www.statslab.cam.ac.uk/~grg/teaching/peres99probability.pdf
    14 Dec 2005: "!$#&%'() ,. -. /10 2&354 6798"79:. ;=<?>A@CBEDF<AGIHJ@K@CLJ<NMOHEPQR@TSVUXWOBEDYMZBE[[<]DMV>_LJWWVUbaOcEBdUfegRhdhdijkW_@l<AG5m_DF<_mH]DF<?npo"Pf@qLsrKPt[NPX@CDuPvGIwkHx@ly?WOBEDzHJG)H{QJn|rHx}EPn;<A}dPtQ. ]]{_{Rdd! "$#%&' )(", "-&.0/21

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