धन उगाहना 15 सितंबर, 2024 – 1 अक्टूबर, 2024 धन उगाहने के अभियान के बारे में

Kernel Smoothing: Principles, Methods and Applications

Main
Mathematics
Kernel Smoothing: Principles, Methods...

Kernel Smoothing: Principles, Methods and Applications

Sucharita Ghosh

0 / 5.0

यह पुस्तक आपको कितनी अच्छी लगी?

फ़ाइल की गुणवत्ता क्या है?

पुस्तक की गुणवत्ता का मूल्यांकन करने के लिए यह पुस्तक डाउनलोड करें

डाउनलोड की गई फ़ाइलों की गुणवत्ता क्या है?

श्रेणियाँ:

साल:

2018

संस्करण:

1

प्रकाशन:

Wiley

भाषा:

english

पृष्ठ:

272

ISBN 10:

111845605X

ISBN 13:

9781118456057

फ़ाइल:

PDF, 1.52 MB

IPFS:

,

english, 2018

ऑनलाइन पढ़ें

में रूपांतरण जारी है

में रूपांतरण विफल रहा

आप के लिए दिलचस्प हो सकता है

Илия Георгиев Илиев; — Извори за българската история XXX

Adrian W, Bowman Adelchi Azzalini — Applied Smoothing Techniques for Data Analysis: The Kernel Approach with S-Plus Illustrations

Ralf Herbrich — Learning Kernel Classifiers: Theory and Algorithms

Frédéric Ferraty, Philippe Vieu — Nonparametric Functional Data Analysis.

Michael R. Kosorok — Introduction to empirical processes and semiparametric inference

M. P. Wand, M. C. Jones (auth.) — Kernel Smoothing

Jussi Klemela — Smoothing of Multivariate Data: Density Estimation and Visualization (Wiley Series in Probability and Statistics)

David W. Scott — Multivariate Density Estimation: Theory, Practice, and Visualization

David Ruppert, M. P. Wand, R. J. Carroll — Semiparametric regression

John Shawe-Taylor, Nello Cristianini — Kernel Methods for Pattern Analysis

Nello Cristianini, John Shawe-Taylor — An Introduction to Support Vector Machines and Other Kernel-based Learning Methods

Wolfgang Härdle — Applied Nonparametric Regression

Nello Cristianini, John Shawe-Taylor — An Introduction to Support Vector Machines and Other Kernel-based Learning Methods

Randall L. Eubank — Nonparametric Regression and Spline Smoothing

S. Y. Kung — Kernel Methods and Machine Learning

Fomin, Fedor V.; Lokshtanov, Daniel; Saurabh, Saket; Zehavi, Meirav et al. — Kernelization: theory of parameterized preprocessing

Vern I. Paulsen, Mrinal Raghupathi — An Introduction to the Theory of Reproducing Kernel Hilbert Spaces

B. W. Silverman — Density estimation for statistics and data analysis

José E. Chacón, Tarn Duong — Multivariate Kernel Smoothing and Its Applications

Elaine Cohen, Richard F. Riesenfeld, Gershon Elber — Geometric Modeling with Splines: An Introduction

Masayuki Hirukawa — Asymmetric Kernel Smoothing

Ivanka Horova, Jan Kolacek, Jiri Zelinka — Kernel Smoothing in MATLAB: Theory and Practice of Kernel Smoothing

Sucharita Ghosh — Kernel Smoothing Principles Methods And Applications

T. Amemiya, A.R. Gallant, J.F. Geweke, C. Hsiao, P. Robinson, A. Zellner — Journal of Econometrics (2011) Vol.162 N°2

Wolfgang H¨ardle — Applied Nonparametric Regression

Wolfgang H¨ardle — Applied Nonparametric Regression

Wolfgang H¨ardle — Applied Nonparametric Regression

Wolfgang H¨ardle — Applied Nonparametric Regression

Wolfgang H¨ardle — Applied Nonparametric Regression

Daniel J. Henderson; Christopher F. Parmeter — Applied Nonparametric Econometrics

Subir Ghosh (Editor) — Asymptotics, Nonparametrics, and Time Series

Jianqing Fan, Qiwei Yao — Nonlinear time series: Nonparametric and Parametric Methods

Larry Wasserman — All of Nonparametric Statistics

Jeffrey S. Simonoff — Smoothing Methods in Statistics (Springer Series in Statistics)

Jeffrey D. Hart — Nonparametric smoothing and lack-of-fit tests

Jianqing Fan, Qiwei Yao — Nonlinear Time Series: Nonparametric and Parametric Methods

M. P. Wand, M. C. Jones (auth.) — Kernel Smoothing

Fan J., Gijbels I. — Local polynomial modelling and its applications

Michael G. Akritas and Dimitris N. Politis (Eds.) — Recent Advances and Trends in Nonparametric Statistics

Markovich, Natalia — Nonparametric Analysis of Univariate Heavy-Tailed Data: Research and Practice

Michael G. Schimek — Smoothing and Regression: Approaches, Computation, and Application

David W. Scott — Multivariate density estimation: theory, practice, and visualization

सबसे उपयोगी शब्द