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1 - 10 of 17 search results for katalk:PC53 24 / |u:www.statslab.cam.ac.uk where 0 match all words and 17 match some words.

  1. Results that match 1 of 2 words

  2. oheads_lectures.dvi

    www.statslab.cam.ac.uk/~rrw1/opt/oheads_lectures4up.pdf
    28 Apr 2010: j=31. xij 1,. 14. j=11. xij 26. j=24. xij 1,. 30. ... 36.1FI 31.2FF 27.7HA 22.6HC 38.6MS 12.5MI 73.7BS. 51.7PI 18.6OJ 29.7QP 4.0GS 24.6SM 30.4SE 5.7TK = CARB;.

  3. oheads_lectures.dvi

    www.statslab.cam.ac.uk/~rrw1/opt/oheads_lectures.pdf
    28 Apr 2010: j=31. xij 1,. 14. j=11. xij 26. j=24. xij 1,. 30. ... 36.1FI 31.2FF 27.7HA 22.6HC 38.6MS 12.5MI 73.7BS. 51.7PI 18.6OJ 29.7QP 4.0GS 24.6SM 30.4SE 5.7TK = CARB;.

  4. History of the Diet Problem

    www.statslab.cam.ac.uk/~rrw1/opt/diet_history.html
    15 Apr 2010: Stigler's guess for the optimal solution was off by only 24 cents per year.

  5. L.dvi

    www.statslab.cam.ac.uk/~rrw1/oc/L2010a4.pdf
    25 Nov 2010: 236.5 Calculation of the Gittins index. 24. 6.6 Forward induction policies. ... 24. 7 Average-cost Programming 257.1 Average-cost optimization. 257.2 Example: admission control at a queue.

  6. Maximum likelihood estimation of a multidimensional log-concave…

    www.statslab.cam.ac.uk/~rjs57/CSSFinalLV.pdf
    24 Mar 2010: n = 100 n = 200 n = 500 n = 1000 n = 2000d = 2 1.5 secs (260) 2.9 secs (500) 50 secs (1270) 4 mins (2540) 24 mins (5370)d = 3 6

  7. ODE approximations to some Markov chain models Perla Sousi ...

    www.statslab.cam.ac.uk/~ps422/smithknight1.pdf
    10 Nov 2010: 23. 4.2.2 Notation. 24. 4.2.3 Defining the rates of individual interactions. ... 24. 4.2.4 Deriving the Markov chain rates. 25. 4.2.5 Example: n = 1.

  8. VERY BRIEF INTRODUCTION TOSTATISTICAL MODELLING IN RP.M.E.Altham,…

    www.statslab.cam.ac.uk/~pat/littleintro.pdf
    24 Aug 2010: am.a. ukhttp://www.statslab. am.a. uk/patFIRST CLASS IS MONDAY JAN 24, 2005. YOU NEED TO SIGN UP FORONE OF THE SLOTS 10-11 am, 11-12 noon, 12

  9. IMS CollectionsHigh Dimensional Probability V: The Luminy VolumeVol.…

    www.statslab.cam.ac.uk/~nickl/Site/__files/IMSCOLL522.pdf
    26 Feb 2010: 24) ch(p, q) ‖p q‖2,λ Ch(p, q). holds for p, q P (t, ζ, D) with t > 1/2 and ζ > 0 (cf. ... Consequently, us-ing (24), the Hellinger-bracketing metric entropy H[](ε, P̄H(n), ‖ ‖2,λ) (with P̄H(n) ={ p : p P̃H(n) }) can be bounded by the L2(T

  10. Adaptive estimation of a distribution function and its density in…

    www.statslab.cam.ac.uk/~nickl/Site/__files/BEJ239.pdf
    19 Nov 2010: F. Combining the bounds completes the proof of (24).It remains to prove (25). ... By (19) and (27), we have V ′ c2(λ)nσ 2, and the condition on t together with (24) givesthe result.

  11. Confidence bands in density estimation

    www.statslab.cam.ac.uk/~nickl/Site/__files/AOS738.pdf
    19 Feb 2010: The Annals of Statistics2010, Vol. 38, No. 2, 1122–1170DOI: 10.1214/09-AOS738 Institute of Mathematical Statistics, 2010. CONFIDENCE BANDS IN DENSITY ESTIMATION. BY EVARIST GINÉ AND RICHARD NICKL. University of Connecticut and University of

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