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Record Nr. |
UNINA9910789721903321 |
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Autore |
Matloff Norman S |
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Titolo |
The art of R programming [[electronic resource] ] : a tour of statistical software design / / by Norman Matloff |
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Pubbl/distr/stampa |
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San Francisco, : No Starch Press, 2011 |
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ISBN |
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Edizione |
[1st edition] |
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Descrizione fisica |
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1 online resource (404 p.) |
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Disciplina |
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Soggetti |
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Statistics - Data processing |
R (Computer program language) |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Nota di contenuto |
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Brief Contents; Contents in Detail; Acknowledgments; Introduction; Why Use R for Your Statistical Work?; Whom Is This Book For?; My Own Background; 1: Getting Started; 1.1 How to Run R; 1.2 A First R Session; 1.3 Introduction to Functions; 1.4 Preview of Some Important R Data Structures; 1.5 Extended Example: Regression Analysis of Exam Grades; 1.6 Startup and Shutdown; 1.7 Getting Help; 2: Vectors; 2.1 Scalars, Vectors, Arrays, and Matrices; 2.2 Declarations; 2.3 Recycling; 2.4 Common Vector Operations; 2.5 Using all() and any(); 2.6 Vectorized Operations; 2.7 NA and NULL Values |
2.8 Filtering2.9 A Vectorized if-then-else: The ifelse() Function; 2.10 Testing Vector Equality; 2.11 Vector Element Names; 2.12 More on c(); 3: Matrices and Arrays; 3.1 Creating Matrices; 3.2 General Matrix Operations; 3.3 Applying Functions to Matrix Rows and Columns; 3.4 Adding and Deleting Matrix Rows and Columns; 3.5 More on the Vector/Matrix Distinction; 3.6 Avoiding Unintended Dimension Reduction; 3.7 Naming Matrix Rows and Columns; 3.8 Higher-Dimensional Arrays; 4: Lists; 4.1 Creating Lists; 4.2 General List Operations; 4.3 Accessing List Components and Values |
4.4 Applying Functions to Lists4.5 Recursive Lists; 5: Data Frames; 5.1 Creating Data Frames; 5.2 Other Matrix-Like Operations; 5.3 Merging Data Frames; 5.4 Applying Functions to Data Frames; 6: Factors and Tables; 6.1 Factors and Levels; 6.2 Common Functions Used with Factors; 6.3 Working with Tables; 6.4 Other Factor- and Table-Related |
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Functions; 7: R Programming Structures; 7.1 Control Statements; 7.2 Arithmetic and Boolean Operators and Values; 7.3 Default Values for Arguments; 7.4 Return Values; 7.5 Functions Are Objects; 7.6 Environment and Scope Issues; 7.7 No Pointers in R |
7.8 Writing Upstairs7.9 Recursion; 7.10 Replacement Functions; 7.11 Tools for Composing Function Code; 7.12 Writing Your Own Binary Operations; 7.13 Anonymous Functions; 8: Doing Math and Simulations in R; 8.1 Math Functions; 8.2 Functions for Statistical Distributions; 8.3 Sorting; 8.4 Linear Algebra Operations on Vectors and Matrices; 8.5 Set Operations; 8.6 Simulation Programming in R; 9: Object-Oriented Programming; 9.1 S3 Classes; 9.2 S4 Classes; 9.3 S3 Versus S4; 9.4 Managing Your Objects; 10: Input/Output; 10.1 Accessing the Keyboard and Monitor; 10.2 Reading and Writing Files |
10.3 Accessing the Internet11: String Manipulation; 11.1 An Overview of String-Manipulation Functions; 11.2 Regular Expressions; 11.3 Use of String Utilities in the edtdbg Debugging Tool; 12: Graphics; 12.1 Creating Graphs; 12.2 Customizing Graphs; 12.3 Saving Graphs to Files; 12.4 Creating Three-Dimensional Plots; 13: Debugging; 13.1 Fundamental Principles of Debugging; 13.2 Why Use a Debugging Tool?; 13.3 Using R Debugging Facilities; 13.4 Moving Up in the World: More Convenient DebuggingTools; 13.5 Ensuring Consistency in Debugging Simulation Code; 13.6 Syntax and Runtime Errors |
13.7 Running GDB on R Itself |
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Sommario/riassunto |
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R is the world's most popular programming language for statistical computing. Drug developers use it to evaluate clinical trials and determine which medications are safe and effective; archaeologists use it to sift through mounds of artifacts and track the spread of ancient civilizations; and actuaries use it to assess financial risks and keep economies running smoothly. In The Art of R Programming , veteran author Norman Matloff takes readers on a guided tour of this powerful language, from basic object types and data structures to graphing, parallel processing, and much more. Along the way, |
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2. |
Record Nr. |
UNINA9910787329803321 |
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Autore |
Wang Guanyu (Physicist) |
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Titolo |
Analysis of complex diseases : a mathematical perspective / / Guanyu Wang |
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Pubbl/distr/stampa |
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Boca Raton : , : CRC Press, Taylor & Francis Group, , [2014] |
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�2014 |
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ISBN |
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0-429-07190-6 |
1-4665-7221-3 |
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Descrizione fisica |
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1 online resource (xxi, 196 pages) : illustrations (some color) |
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Collana |
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Disciplina |
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Soggetti |
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Metabolism - Disorders |
Systems biology |
Biological models |
Genetic disorders |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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Food intake and energy metabolism -- Glucose homeostasis -- Optimal glucose homeostasis -- Bistability as a fundamental phenomenon -- Biomolecular network -- P13K-AKT-TOR pathway -- Diseases related to metabolism -- Mathematical modeling of the P13K-AKT-TOR Pathway -- Fundamental decomposition -- Normal phenotype -- Disease phenotypes -- Tao of diseases. |
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Sommario/riassunto |
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A complex disease involves many etiological and risk factors operating at multiple levels-molecular, cellular, organismal, and environmental. The incidence of such diseases as cancer, obesity, and diabetes are increasing in occurrence, urging us to think fundamentally and use a broader perspective to identify their connection and revolutionize treatments. The understanding of biological data derived from studying diseases can be enhanced by theories and mathematical models, which clarify the big picture and help to reveal the overarching mechanisms that govern complex biological phenomena.< |
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