Spatial Statistics: Methodological Aspects and Applications: Lecture Notes in Statistics, cartea 159
Editat de Marc Mooreen Limba Engleză Paperback – 9 mar 2001
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Specificații
ISBN-13: 9780387952406
ISBN-10: 0387952403
Pagini: 304
Ilustrații: XVI, 308 p. 26 illus.
Dimensiuni: 155 x 235 x 17 mm
Greutate: 0.46 kg
Ediția:2001
Editura: Springer
Colecția Lecture Notes in Statistics
Seria Lecture Notes in Statistics
Locul publicării:New York, NY, United States
ISBN-10: 0387952403
Pagini: 304
Ilustrații: XVI, 308 p. 26 illus.
Dimensiuni: 155 x 235 x 17 mm
Greutate: 0.46 kg
Ediția:2001
Editura: Springer
Colecția Lecture Notes in Statistics
Seria Lecture Notes in Statistics
Locul publicării:New York, NY, United States
Public țintă
ResearchCuprins
1 Asymptotic Distribution of t he Empirical Cumulative Distribution Function Predictor under N onstationarity.- 1 Introduction.- 2 Th e Asymptotic Framework.- 3 Main Results.- 4 Proofs.- 5 References.- 2 Robustness Problems in the Analysis of Spatial Data.- 1 Introduction.- 2 Highly Robust Variogram Estimation.- 3 Variogram Model Selection.- 4 Variogram Fitting by Generalized Least Squares.- 5 Conclusion.- 6 References.- 3 Standards Adoption Dynamics and Test for Nonspatial Coordination.- 1 Introduction.- 2 Models with out Spatial Coordination.- 3 Models with Spatial Coordination.- 4 Tests for Nonspatial Coordination : the Case of a Regular Lattice with v Nearest Neighbours.- 5 References.- 4 Random Fields on Zd, Limit Theorems and Irregular Sets.- 1 Introduction.- 2 CLT for Weakly Dependent Stationary Random Fields over Irregular Sets.- 3 CLT for % MathType!MTEF!2!1!+-% feaagCart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaamiwamaaBa% aaleaacaWGUbaabeaakiabg2da9iabeA8aQnaabmaabaGaeqOVdG3a% aSbaaSqaaiaad6gaaeqaaOGaaiilaiaadMfadaWgaaWcbaGaamOBaa% qabaaakiaawIcacaGLPaaaaaa!41E9!$${X_n} = \varphi \left( {{\xi _n},{Y_n}} \right)$$.- 4 The Same Program for High-Level Exceedances.- 5 References.- 5 Multiscale Graphical Modeling in Space: Applications to Command and Control.- 1 Introduction.- 2 Tree-Struct ured Markov Models.- 3 Graphical Markov Models.- 4 Multiscale Graphical Models.- 5 Discussion.- 6 References.- 6 Unsupervised Image Segmentation Using a Telegraph Parameterization of Pickard Random Field.- 1 Introduction.- 2 Approach.- 3 EM ReestimationFormulas for Parameter Estimation 119.- 4 3D extension.- 5 Telegraph model.- 6 Mixture of Gaussians.- 7 Results.- 8 Conclusion.- 9 References.- 7 Estimation of Motion from Sequences of Images.- 1 Introduction.- 2 Data.- 3 The Continuity Equation.- 4 Projection from t he Sphere to th e Plane.- 5 Parametrization of the Displacement Field.- 6 Discretization of the Continuity Equation.- 7 Penalized Least Squares Estimation.- 8 Estimation of the Variance of the Observation Error.- 9 Asymptotics.- 10 Application to Ozone Images.- 11 Conclusion.- 12 References.- 8 Applications of Random Fields in Human Brain Mapping.- 1 Introduction.- 2 Test Statistics.- 3 Distribution of the Test Statistics Based on Random Field Theory.- 4 Results.- 5 Conclusion.- 6 References.- 9 In Praise of Tedious Permutation.- 1 R.A. Fisher (1890–1962) , the Anthropologist s and Darwin’s Peas.- 2 Permutation Tests in Human Brain Mapping.- 3 Permutation Tests of Spatial Statistics.- 4 Some Limitations of Permutation Testing.- 5 Conclusion.- 6 References.- 10 Group Analysis of Individual Activation Maps Using 3D Scale-Space Primal Sketches and a Markovian Random Field.- 1 Introduction.- 2 Method.- 3 Results.- 4 Conclusion.- 5 References.- 11 Some Statistical Aspects of Magnetoencephalography.- 1 Introduction.- 2 Outlines of MEG Source Analysis.- 3 Spatial Statistics of the Measurement Noise.- 4 Localized Averages.- 5 Selected Aspects of Nonlinear Parameter Estimation Problems.- 6 Concluding Remarks.- 7 References.- 12 Statistics of Nonlinear Spatial Distortions in Histological Images.- 1 Introduction.- 2 Theory.- 3 Concerning the Application of the Central Limit Theorem.- 4 Conclusion.- 5 References.- 13 Statistical Analysis of Brain Maps: Some Lessons from Morphometries.- 1 Introduction.- 2 The Coreof Modern Morphometries: An Overview.- 3 Partial Least Squares for Correlations of Shape.- 4 Symmetry.- 5 Varieties of “Localization” for Image Phenomena.- 6 Concluding Remarks.- 7 References.