Author: Hiroshi Akima
Publisher:
ISBN:
Category : Interpolation
Languages : en
Pages : 40
Book Description
A Method of Smooth Curve Fitting
Author: Hiroshi Akima
Publisher:
ISBN:
Category : Interpolation
Languages : en
Pages : 40
Book Description
Publisher:
ISBN:
Category : Interpolation
Languages : en
Pages : 40
Book Description
A Method of Bivariate Interpolation and Smooth Surface Fitting Based on Local Procedures
Author: Hiroshi Akima
Publisher:
ISBN:
Category : Interpolation
Languages : en
Pages : 52
Book Description
Publisher:
ISBN:
Category : Interpolation
Languages : en
Pages : 52
Book Description
Fitting Models to Biological Data Using Linear and Nonlinear Regression
Author: Harvey Motulsky
Publisher: Oxford University Press
ISBN: 9780198038344
Category : Mathematics
Languages : en
Pages : 352
Book Description
Most biologists use nonlinear regression more than any other statistical technique, but there are very few places to learn about curve-fitting. This book, by the author of the very successful Intuitive Biostatistics, addresses this relatively focused need of an extraordinarily broad range of scientists.
Publisher: Oxford University Press
ISBN: 9780198038344
Category : Mathematics
Languages : en
Pages : 352
Book Description
Most biologists use nonlinear regression more than any other statistical technique, but there are very few places to learn about curve-fitting. This book, by the author of the very successful Intuitive Biostatistics, addresses this relatively focused need of an extraordinarily broad range of scientists.
Introduction to Data Science
Author: Rafael A. Irizarry
Publisher: CRC Press
ISBN: 1000708039
Category : Mathematics
Languages : en
Pages : 836
Book Description
Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization, predictive algorithm building, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation. This book is a textbook for a first course in data science. No previous knowledge of R is necessary, although some experience with programming may be helpful. The book is divided into six parts: R, data visualization, statistics with R, data wrangling, machine learning, and productivity tools. Each part has several chapters meant to be presented as one lecture. The author uses motivating case studies that realistically mimic a data scientist’s experience. He starts by asking specific questions and answers these through data analysis so concepts are learned as a means to answering the questions. Examples of the case studies included are: US murder rates by state, self-reported student heights, trends in world health and economics, the impact of vaccines on infectious disease rates, the financial crisis of 2007-2008, election forecasting, building a baseball team, image processing of hand-written digits, and movie recommendation systems. The statistical concepts used to answer the case study questions are only briefly introduced, so complementing with a probability and statistics textbook is highly recommended for in-depth understanding of these concepts. If you read and understand the chapters and complete the exercises, you will be prepared to learn the more advanced concepts and skills needed to become an expert.
Publisher: CRC Press
ISBN: 1000708039
Category : Mathematics
Languages : en
Pages : 836
Book Description
Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization, predictive algorithm building, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation. This book is a textbook for a first course in data science. No previous knowledge of R is necessary, although some experience with programming may be helpful. The book is divided into six parts: R, data visualization, statistics with R, data wrangling, machine learning, and productivity tools. Each part has several chapters meant to be presented as one lecture. The author uses motivating case studies that realistically mimic a data scientist’s experience. He starts by asking specific questions and answers these through data analysis so concepts are learned as a means to answering the questions. Examples of the case studies included are: US murder rates by state, self-reported student heights, trends in world health and economics, the impact of vaccines on infectious disease rates, the financial crisis of 2007-2008, election forecasting, building a baseball team, image processing of hand-written digits, and movie recommendation systems. The statistical concepts used to answer the case study questions are only briefly introduced, so complementing with a probability and statistics textbook is highly recommended for in-depth understanding of these concepts. If you read and understand the chapters and complete the exercises, you will be prepared to learn the more advanced concepts and skills needed to become an expert.
Engineering Mathematics - III
Author:
Publisher: Krishna Prakashan Media
ISBN: 9788182830967
Category :
Languages : en
Pages : 832
Book Description
Publisher: Krishna Prakashan Media
ISBN: 9788182830967
Category :
Languages : en
Pages : 832
Book Description
Smoothing Methods in Statistics
Author: Jeffrey S. Simonoff
Publisher: Springer Science & Business Media
ISBN: 1461240263
Category : Mathematics
Languages : en
Pages : 349
Book Description
Focussing on applications, this book covers a very broad range, including simple and complex univariate and multivariate density estimation, nonparametric regression estimation, categorical data smoothing, and applications of smoothing to other areas of statistics. It will thus be of particular interest to data analysts, as arguments generally proceed from actual data rather than statistical theory, while the "Background Material" sections will interest statisticians studying the field. Over 750 references allow researchers to find the original sources for more details, and the "Computational Issues" sections provide sources for statistical software that use the methods discussed. Each chapter includes exercises with a heavily computational focus based upon the data sets used in the book, making it equally suitable as a textbook for a course in smoothing.
Publisher: Springer Science & Business Media
ISBN: 1461240263
Category : Mathematics
Languages : en
Pages : 349
Book Description
Focussing on applications, this book covers a very broad range, including simple and complex univariate and multivariate density estimation, nonparametric regression estimation, categorical data smoothing, and applications of smoothing to other areas of statistics. It will thus be of particular interest to data analysts, as arguments generally proceed from actual data rather than statistical theory, while the "Background Material" sections will interest statisticians studying the field. Over 750 references allow researchers to find the original sources for more details, and the "Computational Issues" sections provide sources for statistical software that use the methods discussed. Each chapter includes exercises with a heavily computational focus based upon the data sets used in the book, making it equally suitable as a textbook for a course in smoothing.
NOAA Technical Report ERL.
Author: United States. National Oceanic and Atmospheric Administration
Publisher:
ISBN:
Category :
Languages : en
Pages : 40
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 40
Book Description
A Method of Bivariate Interpolation and Smooth Surface Fitting for Values Given at Irregularly Distributed Points
Author: Hiroshi Akima
Publisher:
ISBN:
Category : Interpolation
Languages : en
Pages : 64
Book Description
Publisher:
ISBN:
Category : Interpolation
Languages : en
Pages : 64
Book Description
ESSA Technical Report ERL-ITS.
Author:
Publisher:
ISBN:
Category : Meteorology
Languages : en
Pages : 40
Book Description
Publisher:
ISBN:
Category : Meteorology
Languages : en
Pages : 40
Book Description
ESSA Technical Report ERL.
Author: United States. Environmental Science Services Administration
Publisher:
ISBN:
Category :
Languages : en
Pages : 40
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 40
Book Description