Главная    Ex Libris    Книги    Журналы    Статьи    Серии    Каталог    Wanted    Загрузка    ХудЛит    Справка    Поиск по индексам    Поиск    Форум   
blank
Авторизация

       
blank
Поиск по указателям

blank
blank
blank
Красота
blank
Bosq D. — Nonparametric statistics for stochastic processes
Bosq D. — Nonparametric statistics for stochastic processes



Обсудите книгу на научном форуме



Нашли опечатку?
Выделите ее мышкой и нажмите Ctrl+Enter


Название: Nonparametric statistics for stochastic processes

Автор: Bosq D.

Аннотация:

This book is devoted to the theory and applications of nonparametic functional estimation and prediction. Chapter 1 provides an overview of inequalities and limit theorems for strong mixing processes. Density and regression estimation in discrete time are studied in Chapter 2 and 3. The special rates of convergence which appear in continuous time are presented in Chapters 4 and 5. This second edition is extensively revised and it contains two new chapters. Chapter 6 discusses the surprising local time density estimator. Chapter 7 gives a detailed account of implementation of nonparametric method and practical examples in economics, finance and physics. Comarison with ARMA and ARCH methods shows the efficiency of nonparametric forecasting. The prerequisite is a knowledge of classical probability theory and statistics. Denis Bosq is Professor of Statistics at the Unviersity of Paris 6 (Pierre et Marie Curie). He is Editor-in-Chief of "Statistical Inference for Stochastic Processes" and an editor of "Journal of Nonparametric Statistics". He is an elected member of the International Statistical Institute. He has published about 90 papers or works in nonparametric statistics and four books.


Язык: en

Рубрика: Математика/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Год издания: 1996

Количество страниц: 169

Добавлена в каталог: 04.12.2005

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID
blank
Предметный указатель
$m$-dependent      17
$p$-adic Process      56
$\alpha$-mixing      7 16
$\beta$-mixing      16
$\varphi$- mixing      16
$\varphi_{rev}$-mixing      78 142
Absolute regularity      16
Adaptive method      14
Admissible sampling      13 122 139
ARMA process      1 92
Asymptotic normality      9 11 34 52 73 78 95 137
Autoregressive processes (infinite dimensional)      14
Berbee’s lemma      17
Bernstein’s inequality      22
Billingley’s inequality      20
Bochner's lemma      42 43
Borel — Cantelli lemma in continuous time      111
Box — Cox transformation      85
Box — Jenkins (method)      1 92
Bradley’s lemma      18
Cadlag      96 121
Cars registrations      144 153 155
Central limit theorem      34
Chaos      84
Chaotic data      55
Coupling      17
Covariance inequalities      18 19
Cramer’s conditions      22
Cross validation      90
Davydov’s inequality      20
Density kernel estimator      3 40 95
Deseasonalization      14 86—87
Dichotomy      119 139
Differencing      12 87
Differentiable sample paths      108
Diffusion process      105
Double kernel method      91
Dynamical system      56
Electricity consumption      93 144 156
Elimination of trend and seasonality      86
Empirical measure      40 66 95
Epanechnikov kernel      40 91
Errors in variables (processes with)      61—62 84—85
Exogeneous variables      14 92 93
Exponential type inequalities      7 22—31
Forecasting      see Prediction
Full rate      108
Gaussian process      10 17 72 105 108 120
General stationary processes (prediction for)      79
Geometrically strongly mixing (GSM) processes      44 96
histogram      3
Hoeffding’s Inequality      22
Image measure theorem      107
Implementation of nonparametric method      85—93
Intermediate rates      106
Interpolator      83
Irregular sampling      122 139
Kernel      39
Kernel of order ($k$, $\lambda$)      96
Kolmogorov Extension Theorem      4
Large deviations inequalities      7 22—31
Law of Large Numbers      31—34
Linear process      16 44
Logistic trend      82
Markov process      17 74 140
Markov process of order      74
Martingale      80
minimax      9 44 102 103 106
MISE      89
Mixing      7 15
Mixture      4
Naive kernel      3 40
Nonparametric predictor      1 6 74 79 91 140
Nonstationary process (prediction for)      80
Optimal rate      8
Ornstein — Uhlenbeck process      123
Outliers detection      83
Parametric predictors      92
Parametric rate      10
Periodic      81
Plug-in method      88
Pollution      93
Pseudo-regression      82
Quadratic error (asymptotic)      41 67 97 131
Rate      31
Regression kernel estimator      67 130
Regression with error      84
Regressogram      5
Rio’s inequality      18
Robust      5 14
Sampling      13 14 119 139
SARIMA process      1
Seasonality      12 13 14 86 93
Semiparametric      14
Similarity      13
Singular distribution      59
Stationary process      7
Statistical error of prediction      6
Superoptimal rate      10 103 106 111 117 122 134 142
Trend      86
Two-$\alpha$-mixing      17 41
Uniform convergence      8 10 11 44 70 111 138
Variance (stabilization of)      85
Wavelets      14 127
blank
Реклама
blank
blank
HR
@Mail.ru
       © Электронная библиотека попечительского совета мехмата МГУ, 2004-2020
Электронная библиотека мехмата МГУ | Valid HTML 4.01! | Valid CSS! О проекте