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Asymptotics and optimal bandwidth selection for highest density…
www.statslab.cam.ac.uk/~rjs57/Samworth10.pdf21 Apr 2010: tn, tj tn], where D4 = 12 μ2(K)f ′′(xj ) D1;. • ... tn = o(n1/6).Then. P(f̂h(x. tj ) < f̂h,τ. ) ( tf ′(xj ) D4n1/2h5/2{R(K)fτ 2D3,j D2}1/2). -
Statistical modellingRajen D. Shah r.shah@statslab.cam.ac.uk Course…
www.statslab.cam.ac.uk/~rds37/teaching/statistical_modelling/notes.pdf14 Feb 2019: and (Xj )TXj = X. Tj (I Pj)Xj = ‖(I Pj)Xj‖2. -
Three theorems in discrete random geometry
www.statslab.cam.ac.uk/~grg/papers/PS_2011_185-rev.pdf27 Jan 2012: The outcome is a decomposition ofγ into an ordered set of bridges with vertical displacements written T0 > T1 > > Tj. ... Therefore,. Z(x) 2. Ti<<T1T0>>Tj. j. k=i. ζxTk = 2. T =1. -
Mathematics of Operational Research Contents Table of Contents i ...
www.statslab.cam.ac.uk/~rrw1/mor/morweber.pdf15 Mar 2016: Mathematics of Operational Research. Contents. Table of Contents i. Schedules v. 1 Lagrangian Methods 11.1 Lagrangian methods. 11.2 The Lagrange dual. 31.3 Supporting hyperplanes. 3. 2 Convex and Linear Optimization 62.1 Convexity and strong duality. -
Leverage Mendelian Randomization to Learn MeaningfulRepresentations…
www.statslab.cam.ac.uk/~qz280/talk/lmrl-2021/slides.pdf3 Jun 2024: ψ(ρ)1 (β,τ. 2) =. pj=1. ( β. tj)ψ(tj ),. ψ(ρ)2 (β,τ. ... 2) =. pj=1. tj ψ(tj ) E[Tψ(T )], for T N(0, 1). -
41 Paper 1, Section I 7H StatisticsSuppose that X1, ...
www.statslab.cam.ac.uk/~rrw1/stats/StatisticsTriposQuestions.pdf17 Sep 2015: for j 6= i. Prove that the random vectors Yj AjX are independent, and thatY (Y T1 ,. , Y TJ )T has a multivariate normal distribution.[ Hint: Random vectors are independent if -
Simultaneous Hypothesis Testing using Internal Negative Controls…
www.statslab.cam.ac.uk/~qz280/publication/ranc/slides.pdf3 Jun 2024: 2 (Ti)iI (Tj)jInc;3 (Tj)jInc is mutually independent;. 4 (Ti)iI is PRDS on (Ti)iI0;. ... R(t) 1, 0 t 1. Further define. Vnc(t) :=jInc. 1{Tj t}, V̄nc(t) :=n (Vnc(t) 2). -
Cluster detection in networks using percolation
www.statslab.cam.ac.uk/~grg/papers/BEJ412.pdf14 Mar 2013: Patil and Taillie [42]argued that this can be done faster by using the tree structure of Qm, where the root is the entirenetwork Vm and a cluster K Km(tj ) ... is the parent of any cluster L Km(tj 1) such that L K ,where t1 < < tM denote the distinct -
Statistical modellingLecturer: Alberto J. Coca…
www.statslab.cam.ac.uk/~qz280/teaching/modelling-2022/notes_3Dec19.pdf3 Jun 2024: and (Xj )TXj = X. Tj (I Pj)Xj = ‖(I Pj)Xj‖2. -
Random Planar Geometry
www.statslab.cam.ac.uk/~jpm205/teaching/lent2020/rpg_notes.pdf11 Mar 2020: RANDOM PLANAR GEOMETRY. JASON MILLER. Contents. Preface 1. 1. Introduction 1. 2. Plane trees 4. 3. The Brownian excursion 6. 4. Real trees and the Gromov-Hausdorff distance 7. 5. Convergence of discrete trees to the continuum random tree 10. 6.
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