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1. Estimation and Testing Under Sparsity : École d'Été de Probabilités de Saint-Flour XLV – 2015
by Sara van de Geer
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2016
シリーズ名: Lecture Notes in Mathematics ; 2159
オンライン: http://dx.doi.org/10.1007/978-3-319-32774-7
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1 Introduction
The Lasso
3 The square-root Lasso
4 The bias of the Lasso and worst possible sub-directions
5 Confidence intervals using the Lasso
6 Structured sparsity
7 General loss with norm-penalty
8 Empirical process theory for dual norms
9 Probability inequalities for matrices
10 Inequalities for the centred empirical risk and its derivative
11 The margin condition
12 Some worked-out examples
13 Brouwer’s fixed point theorem and sparsity
14 Asymptotically linear estimators of the precision matrix
15 Lower bounds for sparse quadratic forms
16 Symmetrization, contraction and concentration
17 Chaining including concentration
18 Metric structure of convex hulls
1 Introduction
The Lasso
3 The square-root Lasso
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2. Stochastic Geometry, Spatial Statistics and Random Fields : Asymptotic Methods
edited by Evgeny Spodarev
出版情報: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013
シリーズ名: Lecture Notes in Mathematics ; 2068
オンライン: http://dx.doi.org/10.1007/978-3-642-33305-7
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1 Foundations of stochastic geometry and theory of random sets
2 Introduction into integral geometry and stereology
3 Spatial point patterns – models and statistics
4 Asymptotic methods in statistics of random point processes
5 Random tessellations and Cox processes
6 Asymptotic methods for random tessellations
7 Random polytopes
8 Limit theorems in discrete stochastic geometry
9 Introduction to random fields
10 Central limit theorems for weakly dependent random fields
11 Strong limit theorems for increments of random fields
12 Geometry of large random trees: SPDE approximation
1 Foundations of stochastic geometry and theory of random sets
2 Introduction into integral geometry and stereology
3 Spatial point patterns – models and statistics
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3. Parameter Estimation in Stochastic Differential Equations
by Jaya P. N. Bishwal
出版情報: Berlin, Heidelberg : Springer-Verlag Berlin Heidelberg, 2008
シリーズ名: Lecture Notes in Mathematics ; 1923
オンライン: http://dx.doi.org/10.1007/978-3-540-74448-1
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4. Concentration Inequalities and Model Selection : Ecole d'Ete de Probabilites de Saint-Flour XXXIII - 2003
by Pascal Massart ; edited by Jean Picard
出版情報: Berlin, Heidelberg : Springer-Verlag Berlin Heidelberg, 2007
シリーズ名: Lecture Notes in Mathematics ; 1896
オンライン: http://dx.doi.org/10.1007/978-3-540-48503-2
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