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.
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.
Best Fit Lines & Curves
Author: Alan R. Jones
Publisher: Routledge
ISBN: 1351661442
Category : Business & Economics
Languages : en
Pages : 498
Book Description
Best Fit Lines and Curves, and Some Mathe-Magical Transformations (Volume III of the Working Guides to Estimating & Forecasting series) concentrates on techniques for finding the Best Fit Line or Curve to some historical data allowing us to interpolate or extrapolate the implied relationship that will underpin our prediction. A range of simple ‘Moving Measures’ are suggested to smooth the underlying trend and quantify the degree of noise or scatter around that trend. The advantages and disadvantages are discussed and a simple way to offset the latent disadvantage of most Moving Measure Techniques is provided. Simple Linear Regression Analysis, a more formal numerical technique that calculates the line of best fit subject to defined ‘goodness of fit’ criteria. Microsoft Excel is used to demonstrate how to decide whether the line of best fit is a good fit, or just a solution in search of some data. These principles are then extended to cover multiple cost drivers, and how we can use them to quantify 3-Point Estimates. With a deft sleight of hand, certain commonly occurring families of non-linear relationships can be transformed mathe-magically into linear formats, allowing us to exploit the powers of Regression Analysis to find the Best Fit Curves. The concludes with an exploration of the ups and downs of seasonal data (Time Series Analysis). Supported by a wealth of figures and tables, this is a valuable resource for estimators, engineers, accountants, project risk specialists as well as students of cost engineering.
Publisher: Routledge
ISBN: 1351661442
Category : Business & Economics
Languages : en
Pages : 498
Book Description
Best Fit Lines and Curves, and Some Mathe-Magical Transformations (Volume III of the Working Guides to Estimating & Forecasting series) concentrates on techniques for finding the Best Fit Line or Curve to some historical data allowing us to interpolate or extrapolate the implied relationship that will underpin our prediction. A range of simple ‘Moving Measures’ are suggested to smooth the underlying trend and quantify the degree of noise or scatter around that trend. The advantages and disadvantages are discussed and a simple way to offset the latent disadvantage of most Moving Measure Techniques is provided. Simple Linear Regression Analysis, a more formal numerical technique that calculates the line of best fit subject to defined ‘goodness of fit’ criteria. Microsoft Excel is used to demonstrate how to decide whether the line of best fit is a good fit, or just a solution in search of some data. These principles are then extended to cover multiple cost drivers, and how we can use them to quantify 3-Point Estimates. With a deft sleight of hand, certain commonly occurring families of non-linear relationships can be transformed mathe-magically into linear formats, allowing us to exploit the powers of Regression Analysis to find the Best Fit Curves. The concludes with an exploration of the ups and downs of seasonal data (Time Series Analysis). Supported by a wealth of figures and tables, this is a valuable resource for estimators, engineers, accountants, project risk specialists as well as students of cost engineering.
Matrix, Numerical, and Optimization Methods in Science and Engineering
Author: Kevin W. Cassel
Publisher: Cambridge University Press
ISBN: 1108787622
Category : Technology & Engineering
Languages : en
Pages : 728
Book Description
Address vector and matrix methods necessary in numerical methods and optimization of linear systems in engineering with this unified text. Treats the mathematical models that describe and predict the evolution of our processes and systems, and the numerical methods required to obtain approximate solutions. Explores the dynamical systems theory used to describe and characterize system behaviour, alongside the techniques used to optimize their performance. Integrates and unifies matrix and eigenfunction methods with their applications in numerical and optimization methods. Consolidating, generalizing, and unifying these topics into a single coherent subject, this practical resource is suitable for advanced undergraduate students and graduate students in engineering, physical sciences, and applied mathematics.
Publisher: Cambridge University Press
ISBN: 1108787622
Category : Technology & Engineering
Languages : en
Pages : 728
Book Description
Address vector and matrix methods necessary in numerical methods and optimization of linear systems in engineering with this unified text. Treats the mathematical models that describe and predict the evolution of our processes and systems, and the numerical methods required to obtain approximate solutions. Explores the dynamical systems theory used to describe and characterize system behaviour, alongside the techniques used to optimize their performance. Integrates and unifies matrix and eigenfunction methods with their applications in numerical and optimization methods. Consolidating, generalizing, and unifying these topics into a single coherent subject, this practical resource is suitable for advanced undergraduate students and graduate students in engineering, physical sciences, and applied mathematics.
Model Selection and Multimodel Inference
Author: Kenneth P. Burnham
Publisher: Springer Science & Business Media
ISBN: 0387224564
Category : Mathematics
Languages : en
Pages : 512
Book Description
A unique and comprehensive text on the philosophy of model-based data analysis and strategy for the analysis of empirical data. The book introduces information theoretic approaches and focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. It contains several new approaches to estimating model selection uncertainty and incorporating selection uncertainty into estimates of precision. An array of examples is given to illustrate various technical issues. The text has been written for biologists and statisticians using models for making inferences from empirical data.
Publisher: Springer Science & Business Media
ISBN: 0387224564
Category : Mathematics
Languages : en
Pages : 512
Book Description
A unique and comprehensive text on the philosophy of model-based data analysis and strategy for the analysis of empirical data. The book introduces information theoretic approaches and focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. It contains several new approaches to estimating model selection uncertainty and incorporating selection uncertainty into estimates of precision. An array of examples is given to illustrate various technical issues. The text has been written for biologists and statisticians using models for making inferences from empirical data.
Practical Handbook of Curve Fitting
Author: Sandra Arlinghaus
Publisher: CRC Press
ISBN: 1000943283
Category : Mathematics
Languages : en
Pages : 261
Book Description
Practical Handbook of Curve Fitting is a reference work assembled by Arlinghaus and a set of editors with well over a century of combined experience in various disciplines and activities related to curve fitting. The book demonstrates how to analyze World data bases and graph and map the results. Default settings in software packages can produce attractive graphs of data imported into the software. Often, however, the default graph has no equation associated with it and cannot therefore be used as a tool for further analysis or projection of the data. The same software can often be used to generate curves from equations. The reader is shown directly, and in a series of steps, how to fit curves to data using Lotus 1-2-3. There are traditional unbounded curve fitting techniques-lines of least squares, exponentials, logistic curves, and Gompertz curves. There is the bounded curve fitting technique of cubic spline interpolation. Beyond these, there is a detailed application of Feigenbaum's graphical analysis from chaos theory, and there is a hint as to how fractal geometry might come into play. Curve fitting algorithms take on new life when they are actually used on real-world data. They are used in numerous worked examples drawn from electronic data bases of public domain information from the Stars data base of The World Bank and from the WRD data base of the World Resources Institute. The applications are current and reflect a state-of-the-art interest in the human dimensions of global change.
Publisher: CRC Press
ISBN: 1000943283
Category : Mathematics
Languages : en
Pages : 261
Book Description
Practical Handbook of Curve Fitting is a reference work assembled by Arlinghaus and a set of editors with well over a century of combined experience in various disciplines and activities related to curve fitting. The book demonstrates how to analyze World data bases and graph and map the results. Default settings in software packages can produce attractive graphs of data imported into the software. Often, however, the default graph has no equation associated with it and cannot therefore be used as a tool for further analysis or projection of the data. The same software can often be used to generate curves from equations. The reader is shown directly, and in a series of steps, how to fit curves to data using Lotus 1-2-3. There are traditional unbounded curve fitting techniques-lines of least squares, exponentials, logistic curves, and Gompertz curves. There is the bounded curve fitting technique of cubic spline interpolation. Beyond these, there is a detailed application of Feigenbaum's graphical analysis from chaos theory, and there is a hint as to how fractal geometry might come into play. Curve fitting algorithms take on new life when they are actually used on real-world data. They are used in numerous worked examples drawn from electronic data bases of public domain information from the Stars data base of The World Bank and from the WRD data base of the World Resources Institute. The applications are current and reflect a state-of-the-art interest in the human dimensions of global change.
Optimization for Machine Learning
Author: Jason Brownlee
Publisher: Machine Learning Mastery
ISBN:
Category : Computers
Languages : en
Pages : 412
Book Description
Optimization happens everywhere. Machine learning is one example of such and gradient descent is probably the most famous algorithm for performing optimization. Optimization means to find the best value of some function or model. That can be the maximum or the minimum according to some metric. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will learn how to find the optimum point to numerical functions confidently using modern optimization algorithms.
Publisher: Machine Learning Mastery
ISBN:
Category : Computers
Languages : en
Pages : 412
Book Description
Optimization happens everywhere. Machine learning is one example of such and gradient descent is probably the most famous algorithm for performing optimization. Optimization means to find the best value of some function or model. That can be the maximum or the minimum according to some metric. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will learn how to find the optimum point to numerical functions confidently using modern optimization algorithms.
Least Squares Orthogonal Distance Fitting of Curves and Surfaces in Space
Author: Sung Joon Ahn
Publisher: Springer Science & Business Media
ISBN: 3540239669
Category : Computers
Languages : en
Pages : 138
Book Description
Due to the continuing progress of sensor technology, the availability of 3-D cameras is already foreseeable. These cameras are capable of generating a large set of measurement points within a very short time. There are a variety of 3-D camera applications in the fields of robotics, rapid product development and digital factories. In order to not only visualize the point cloud but also to recognize 3-D object models from the point cloud and then further process them in CAD systems, efficient and stable algorithms for 3-D information processing are required. For the automatic segmentation and recognition of such geometric primitives as plane, sphere, cylinder, cone and torus in a 3-D point cloud, efficient software has recently been developed at the Fraunhofer IPA by Sung Joon Ahn. This book describes in detail the complete set of ‘best-?t’ algorithms for general curves and surfaces in space which are employed in the Fraunhofer software.
Publisher: Springer Science & Business Media
ISBN: 3540239669
Category : Computers
Languages : en
Pages : 138
Book Description
Due to the continuing progress of sensor technology, the availability of 3-D cameras is already foreseeable. These cameras are capable of generating a large set of measurement points within a very short time. There are a variety of 3-D camera applications in the fields of robotics, rapid product development and digital factories. In order to not only visualize the point cloud but also to recognize 3-D object models from the point cloud and then further process them in CAD systems, efficient and stable algorithms for 3-D information processing are required. For the automatic segmentation and recognition of such geometric primitives as plane, sphere, cylinder, cone and torus in a 3-D point cloud, efficient software has recently been developed at the Fraunhofer IPA by Sung Joon Ahn. This book describes in detail the complete set of ‘best-?t’ algorithms for general curves and surfaces in space which are employed in the Fraunhofer software.
OpenIntro Statistics
Author: David Diez
Publisher:
ISBN: 9781943450046
Category :
Languages : en
Pages :
Book Description
The OpenIntro project was founded in 2009 to improve the quality and availability of education by producing exceptional books and teaching tools that are free to use and easy to modify. We feature real data whenever possible, and files for the entire textbook are freely available at openintro.org. Visit our website, openintro.org. We provide free videos, statistical software labs, lecture slides, course management tools, and many other helpful resources.
Publisher:
ISBN: 9781943450046
Category :
Languages : en
Pages :
Book Description
The OpenIntro project was founded in 2009 to improve the quality and availability of education by producing exceptional books and teaching tools that are free to use and easy to modify. We feature real data whenever possible, and files for the entire textbook are freely available at openintro.org. Visit our website, openintro.org. We provide free videos, statistical software labs, lecture slides, course management tools, and many other helpful resources.
A Book of Curves
Author: Edward Harrington Lockwood
Publisher: Cambridge University Press
ISBN: 9781001224114
Category : Curves
Languages : en
Pages : 290
Book Description
Describes the drawing of plane curves, cycloidal curves, spirals, glissettes and others.
Publisher: Cambridge University Press
ISBN: 9781001224114
Category : Curves
Languages : en
Pages : 290
Book Description
Describes the drawing of plane curves, cycloidal curves, spirals, glissettes and others.
Circular and Linear Regression
Author: Nikolai Chernov
Publisher: CRC Press
ISBN: 1439835918
Category : Computers
Languages : en
Pages : 285
Book Description
Find the right algorithm for your image processing applicationExploring the recent achievements that have occurred since the mid-1990s, Circular and Linear Regression: Fitting Circles and Lines by Least Squares explains how to use modern algorithms to fit geometric contours (circles and circular arcs) to observed data in image processing and comput
Publisher: CRC Press
ISBN: 1439835918
Category : Computers
Languages : en
Pages : 285
Book Description
Find the right algorithm for your image processing applicationExploring the recent achievements that have occurred since the mid-1990s, Circular and Linear Regression: Fitting Circles and Lines by Least Squares explains how to use modern algorithms to fit geometric contours (circles and circular arcs) to observed data in image processing and comput