標(biāo)題: Titlebook: An Introduction to Statistical Data Science; Theory and Models Giorgio Picci Textbook 2024 The Editor(s) (if applicable) and The Author(s), [打印本頁(yè)] 作者: Buchanan 時(shí)間: 2025-3-21 19:56
書(shū)目名稱An Introduction to Statistical Data Science影響因子(影響力)
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書(shū)目名稱An Introduction to Statistical Data Science網(wǎng)絡(luò)公開(kāi)度
書(shū)目名稱An Introduction to Statistical Data Science網(wǎng)絡(luò)公開(kāi)度學(xué)科排名
書(shū)目名稱An Introduction to Statistical Data Science被引頻次
書(shū)目名稱An Introduction to Statistical Data Science被引頻次學(xué)科排名
書(shū)目名稱An Introduction to Statistical Data Science年度引用
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書(shū)目名稱An Introduction to Statistical Data Science讀者反饋
書(shū)目名稱An Introduction to Statistical Data Science讀者反饋學(xué)科排名
作者: 表示問(wèn) 時(shí)間: 2025-3-21 22:51 作者: PAEAN 時(shí)間: 2025-3-22 00:31
Yuko Hiramatsu,Atsushi Ito,Fumihiro Satoer could be described as “reduced-data” regression and goes under the name of . which has a deep statistical significance. We analyze it both from a probabilistic perspective and from an algorithmic viewpoint.作者: 退潮 時(shí)間: 2025-3-22 08:27
The Question Concerning Technology as Artortant subject with many potential applications. Finally we present a critical view of . a widespread non-linear inference tool which seems to have become the exclusive basic subject of statistical learning.作者: 受辱 時(shí)間: 2025-3-22 11:06
https://doi.org/10.1007/978-3-642-39473-7ad to nonlinear estimation and unique convergence of the algorithms is not guaranteed. Moreover the analysis of these systems requires tools which we do not assume available to the students of this course.作者: 咆哮 時(shí)間: 2025-3-22 14:53
ARX Modeling of Time Series,ad to nonlinear estimation and unique convergence of the algorithms is not guaranteed. Moreover the analysis of these systems requires tools which we do not assume available to the students of this course.作者: Surgeon 時(shí)間: 2025-3-22 17:37 作者: orient 時(shí)間: 2025-3-23 00:20 作者: SPASM 時(shí)間: 2025-3-23 02:25
Principal Component Analysis,er could be described as “reduced-data” regression and goes under the name of . which has a deep statistical significance. We analyze it both from a probabilistic perspective and from an algorithmic viewpoint.作者: strdulate 時(shí)間: 2025-3-23 09:05
Some Nonlinear Inference Problems,ortant subject with many potential applications. Finally we present a critical view of . a widespread non-linear inference tool which seems to have become the exclusive basic subject of statistical learning.作者: 盟軍 時(shí)間: 2025-3-23 09:47 作者: Anthrp 時(shí)間: 2025-3-23 15:16
Virtually Augmented Classroom CurriculumIn this section, we shall just list some basic concepts which are referred to in chapters of this book. The main reference is Shiryaev treatise.作者: ingrate 時(shí)間: 2025-3-23 20:51 作者: 吸氣 時(shí)間: 2025-3-23 23:45
Virtually Augmented Classroom CurriculumA . is a vector space with an inner product . which is complete with respect to the metric induced by the inner product. In other words, every Cauchy sequence has a limit in .. To establish notation, we shall give examples of Hilbert spaces which are used in this book.作者: Condyle 時(shí)間: 2025-3-24 05:36
Introduction,This is an introductory chapter to the statistical approach to Data Science作者: 努力趕上 時(shí)間: 2025-3-24 09:36
Appendix A: Some Facts from Probability Theory,In this section, we shall just list some basic concepts which are referred to in chapters of this book. The main reference is Shiryaev treatise.作者: 規(guī)范就好 時(shí)間: 2025-3-24 14:16 作者: albuminuria 時(shí)間: 2025-3-24 16:07
Appendix C: Facts from Hilbert Space Theory,A . is a vector space with an inner product . which is complete with respect to the metric induced by the inner product. In other words, every Cauchy sequence has a limit in .. To establish notation, we shall give examples of Hilbert spaces which are used in this book.作者: 令人發(fā)膩 時(shí)間: 2025-3-24 21:04
https://doi.org/10.1007/978-3-031-66619-3Statistical Inference; Statistical Methods for Data Science; Statistical Learning; Model Identification作者: Constrain 時(shí)間: 2025-3-25 01:38
978-3-031-66621-6The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl作者: DUST 時(shí)間: 2025-3-25 04:49 作者: hidebound 時(shí)間: 2025-3-25 07:35 作者: 小歌劇 時(shí)間: 2025-3-25 13:23 作者: 裂口 時(shí)間: 2025-3-25 17:53 作者: 胡言亂語(yǔ) 時(shí)間: 2025-3-25 21:47
https://doi.org/10.1007/978-3-642-39476-8 is an a priori information of probabilistic nature about the variable . which is the object of the statistical inference problem. making it a . which, by its very nature, cannot be assigned an exact numerical value. Many problems in econometrics and engineering have a natural formulation in the Bay作者: 遺留之物 時(shí)間: 2025-3-26 00:54 作者: 終止 時(shí)間: 2025-3-26 07:10
The Question Concerning Technology as Artn, which is for example relevant to scene and motion reconstruction in computer vision. A geometric formulation points to a generalization to spherical manifolds of the familiar Gaussian inference on linear-spaces. Next we discuss in some detail non-linear support vector machines which is a very imp作者: Foment 時(shí)間: 2025-3-26 12:05
https://doi.org/10.1007/978-3-642-39473-7 observations indexed by time. Due to errors and various causes of uncertainty these data are random and It is therefore reasonable to model them as .. The scope of the statistical exercise is to discover a stochastic mathematical model of the underlying physical or economic dynamical system for the作者: Afflict 時(shí)間: 2025-3-26 16:40 作者: 勤勞 時(shí)間: 2025-3-26 20:47
Nicolas Jones,Armelle Brun,Anne Boyers from the outset. The technique to solve the problem turns essentially out to be just least squares which, for Gaussian data, can be directly justified based on the maximum likelihood principle. We warn the reader that this is however true only if it is based on strong a priori assumption of noiseless output data and suggest a wide perspective.作者: confederacy 時(shí)間: 2025-3-26 21:06
Tamotsu Mukaiyachi,Toshikazu Katois testing and some traditional applications such as analysis of variance, while the second part points to the “modern” view of linear decision theory centering on linear separability and related algorithms such as the theory of optimal separating hyperplanes. A clever generalization of this idea will lead to nonlinear support vector machines.作者: 燕麥 時(shí)間: 2025-3-27 01:12 作者: 思考才皺眉 時(shí)間: 2025-3-27 07:31
Giorgio PicciPresents statistical concepts, models, methods and techniques for data science.Provides mathematical derivations of algorithms and procedures.Benefits graduate students in applied mathematics and engi作者: 被詛咒的人 時(shí)間: 2025-3-27 12:34
http://image.papertrans.cn/b/image/167426.jpg作者: Adjourn 時(shí)間: 2025-3-27 17:37 作者: 開(kāi)頭 時(shí)間: 2025-3-27 18:21 作者: 寬度 時(shí)間: 2025-3-28 01:47
Linear Hypotheses and Linear Discriminant Analysis,is testing and some traditional applications such as analysis of variance, while the second part points to the “modern” view of linear decision theory centering on linear separability and related algorithms such as the theory of optimal separating hyperplanes. A clever generalization of this idea will lead to nonlinear support vector machines.作者: mighty 時(shí)間: 2025-3-28 04:25
Bayesian Statistics, is an a priori information of probabilistic nature about the variable . which is the object of the statistical inference problem. making it a . which, by its very nature, cannot be assigned an exact numerical value. Many problems in econometrics and engineering have a natural formulation in the Bayesian context.作者: mercenary 時(shí)間: 2025-3-28 07:08 作者: 過(guò)度 時(shí)間: 2025-3-28 10:57 作者: 內(nèi)疚 時(shí)間: 2025-3-28 17:54
A Review of Classical Statistical Inference,eas and the appropriate technical language which will be used for discussing most problems of data science in this book. We discuss statistical estimation and hypothesis testing in a rather elementary although quite general setting. The specializations to linear models will be discussed in the follo作者: FLINT 時(shí)間: 2025-3-28 21:16 作者: 浪蕩子 時(shí)間: 2025-3-28 22:55 作者: Binge-Drinking 時(shí)間: 2025-3-29 06:13
Linear Hypotheses and Linear Discriminant Analysis,is testing and some traditional applications such as analysis of variance, while the second part points to the “modern” view of linear decision theory centering on linear separability and related algorithms such as the theory of optimal separating hyperplanes. A clever generalization of this idea wi作者: 敲竹杠 時(shí)間: 2025-3-29 10:29 作者: excursion 時(shí)間: 2025-3-29 15:15 作者: 是剝皮 時(shí)間: 2025-3-29 17:07
Some Nonlinear Inference Problems,n, which is for example relevant to scene and motion reconstruction in computer vision. A geometric formulation points to a generalization to spherical manifolds of the familiar Gaussian inference on linear-spaces. Next we discuss in some detail non-linear support vector machines which is a very imp作者: 責(zé)任 時(shí)間: 2025-3-29 20:31 作者: objection 時(shí)間: 2025-3-30 00:30
