LEADER 03558nam 2200589Ia 450 001 9910456371803321 005 20200520144314.0 010 $a1-282-75566-8 010 $a9786612755668 010 $a0-12-378606-1 035 $a(CKB)2550000000014106 035 $a(EBL)629953 035 $a(OCoLC)643060708 035 $a(SSID)ssj0000421067 035 $a(PQKBManifestationID)12154533 035 $a(PQKBTitleCode)TC0000421067 035 $a(PQKBWorkID)10407453 035 $a(PQKB)10827941 035 $a(MiAaPQ)EBC629953 035 $a(Au-PeEL)EBL629953 035 $a(CaPaEBR)ebr10408195 035 $a(CaONFJC)MIL275566 035 $a(EXLCZ)992550000000014106 100 $a20091208d2010 uy 0 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt 182 $cc 183 $acr 200 10$aIntroduction to WinBUGS for ecologists$b[electronic resource] $eBayesian approach to regression, ANOVA, mixed models and related analyses /$fMarc Ke?ry 205 $a1st ed. 210 $aAmsterdam ;$aBoston $cElsevier$d2010 215 $a1 online resource (321 p.) 300 $aDescription based upon print version of record. 311 $a0-12-378605-3 320 $aIncludes bibliographical references and index. 327 $aFront Cover; Introduction to WinBUGS for Ecologists; Copyright; Chapter 1. Introduction; Chapter 2. Introduction to the Bayesian Analysis of a Statistical Model; Chapter 3. WinBUGS; Chapter 4. A First Session in WinBUGS: The "Model of the Mean"; Chapter 5. Running WinBUGS from R via R2WinBUGS; Chapter 6. Key Components of (Generalized) Linear Models: Statistical Distributions and the Linear Predictor; Chapter 7. t-Test: Equal and Unequal Variances; Chapter 8. Normal Linear Regression; Chapter 9. Normal One-Way ANOVA; 9.1 Introduction: Fixed and Random Effects; Chapter 10. Normal Two-Way ANOVA 327 $aChapter 11. General Linear Model (ANCOVA)Chapter 12. Linear Mixed-Effects Model; Chapter 13. Introduction to the Generalized Linear Model: Poisson "t-test"; Chapter 14. Overdispersion, Zero-Inflation, and Offsets in the GLM; Chapter 15. Poisson ANCOVA; Chapter 16. Poisson Mixed-Effects Model (Poisson GLMM); Chapter 17. Binomial "t-Test"; Chapter 18. Binomial Analysis of Covariance; Chapter 19. Binomial Mixed-Effects Model (Binomial GLMM); Chapter 20. Nonstandard GLMMs 1: Site-Occupancy Species Distribution Model; Chapter 21. Nonstandard GLMMs 2: Binomial Mixture Model to Model Abundance 327 $aChapter 22. Conclusions Appendix: A List of WinBUGS Tricks 330 $aBayesian statistics has exploded into biology and its sub-disciplines, such as ecology, over the past decade. The free software program WinBUGS and its open-source sister OpenBugs is currently the only flexible and general-purpose program available with which the average ecologist can conduct standard and non-standard Bayesian statistics. Introduction to WINBUGS for Ecologists goes right to the heart of the matter by providing ecologists with a comprehensive, yet concise, guide to applying WinBUGS to the types of models that they use most often: linear (LM), generalized linear (GLM), 606 $aBiometry$xData processing 608 $aElectronic books. 615 0$aBiometry$xData processing. 676 $a577.01/5118 700 $aKe?ry$b Marc$0886459 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910456371803321 996 $aIntroduction to WinBUGS for ecologists$92262565 997 $aUNINA LEADER 03085nam 22004573u 450 001 9910464875403321 005 20210114095621.0 035 $a(CKB)3710000000085963 035 $a(EBL)1561564 035 $a(OCoLC)869281847 035 $a(MiAaPQ)EBC1561564 035 $a(EXLCZ)993710000000085963 100 $a20140421d2014|||| u|| | 101 0 $aeng 135 $aur|n|---||||| 200 10$aHangzhou Lectures on Eigenfunctions of the Laplacian (AM-188)$b[electronic resource] 210 $aPrinceton $cPrinceton University Press$d2014 215 $a1 online resource (206 p.) 225 1 $aAnnals of Mathematics Studies 300 $aDescription based upon print version of record. 311 $a0-691-16078-3 327 $aCover; Title; Copyright; Dedication; Contents; Preface; 1 A review: The Laplacian and the d'Alembertian; 1.1 The Laplacian; 1.2 Fundamental solutions of the d'Alembertian; 2 Geodesics and the Hadamard parametrix; 2.1 Laplace-Beltrami operators; 2.2 Some elliptic regularity estimates; 2.3 Geodesics and normal coordinates-a brief review; 2.4 The Hadamard parametrix; 3 The sharp Weyl formula; 3.1 Eigenfunction expansions; 3.2 Sup-norm estimates for eigenfunctions and spectral clusters; 3.3 Spectral asymptotics: The sharp Weyl formula; 3.4 Sharpness: Spherical harmonics 327 $a3.5 Improved results: The torus3.6 Further improvements: Manifolds with nonpositive curvature; 4 Stationary phase and microlocal analysis; 4.1 The method of stationary phase; 4.2 Pseudodifferential operators; 4.3 Propagation of singularities and Egorov's theorem; 4.4 The Friedrichs quantization; 5 Improved spectral asymptotics and periodic geodesics; 5.1 Periodic geodesics and trace regularity; 5.2 Trace estimates; 5.3 The Duistermaat-Guillemin theorem; 5.4 Geodesic loops and improved sup-norm estimates; 6 Classical and quantum ergodicity; 6.1 Classical ergodicity; 6.2 Quantum ergodicity 330 $a Based on lectures given at Zhejiang University in Hangzhou, China, and Johns Hopkins University, this book introduces eigenfunctions on Riemannian manifolds. Christopher Sogge gives a proof of the sharp Weyl formula for the distribution of eigenvalues of Laplace-Beltrami operators, as well as an improved version of the Weyl formula, the Duistermaat-Guillemin theorem under natural assumptions on the geodesic flow. Sogge shows that there is quantum ergodicity of eigenfunctions if the geodesic flow is ergodic. Sogge begins with a treatment of the Hadamard parametrix before proving the fi 410 0$aAnnals of Mathematics Studies 606 $aEigenfunctions 606 $aLaplacian operator 608 $aElectronic books. 615 4$aEigenfunctions. 615 4$aLaplacian operator. 676 $a515 676 $a515.3533 676 $a515/.3533 700 $aSogge$b Christopher D$0524956 801 0$bAU-PeEL 801 1$bAU-PeEL 801 2$bAU-PeEL 906 $aBOOK 912 $a9910464875403321 996 $aHangzhou Lectures on Eigenfunctions of the Laplacian (AM-188)$91937575 997 $aUNINA