It takes the average reader 1 hour and 30 minutes to read Identifiability and Regression Analysis of Biological Systems Models by Paola Lecca
Assuming a reading speed of 250 words per minute. Learn more
This richly illustrated book presents the objectives of, and the latest techniques for, the identifiability analysis and standard and robust regression analysis of complex dynamical models. The book first provides a definition of complexity in dynamic systems by introducing readers to the concepts of system size, density of interactions, stiff dynamics, and hybrid nature of determination. In turn, it presents the mathematical foundations of and algorithmic procedures for model structural and practical identifiability analysis, multilinear and non-linear regression analysis, and best predictor selection. Although the main fields of application discussed in the book are biochemistry and systems biology, the methodologies described can also be employed in other disciplines such as physics and the environmental sciences. Readers will learn how to deal with problems such as determining the identifiability conditions, searching for an identifiable model, and conducting their own regression analysis and diagnostics without supervision. Featuring a wealth of real-world examples, exercises, and codes in R, the book addresses the needs of doctoral students and researchers in bioinformatics, bioengineering, systems biology, biophysics, biochemistry, the environmental sciences and experimental physics. Readers should be familiar with the fundamentals of probability and statistics (as provided in first-year university courses) and a basic grasp of R.
Identifiability and Regression Analysis of Biological Systems Models by Paola Lecca is 90 pages long, and a total of 22,500 words.
This makes it 30% the length of the average book. It also has 27% more words than the average book.
The average oral reading speed is 183 words per minute. This means it takes 2 hours and 2 minutes to read Identifiability and Regression Analysis of Biological Systems Models aloud.
Identifiability and Regression Analysis of Biological Systems Models is suitable for students ages 10 and up.
Note that there may be other factors that effect this rating besides length that are not factored in on this page. This may include things like complex language or sensitive topics not suitable for students of certain ages.
When deciding what to show young students always use your best judgement and consult a professional.
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