Developing Statistical Software in Fortran 95 1st Edition by David R Lemmon, Joseph L Schafer ISBN 0387281231 9780387281230

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ISBN 10: 0387281231 
ISBN 13: 9780387281230
Author: David R Lemmon, Joseph L Schafer

Many books teach computational statistics. Until now, however, none has shown how to write a good program. This book gives statisticians, biostatisticians and methodologically-oriented researchers the tools they need to develop high-quality statistical software. Topics include how to: Program in Fortran 95 using a pseudo object-oriented style Write accurate and efficient computational procedures Create console applications Build dynamic-link libraries (DLLs) and Windows-based software components Develop graphical user interfaces (GUIs) Through detailed examples, readers are shown how to call Fortran procedures from packages including Excel, SAS, SPSS, S-PLUS, R, and MATLAB. They are even given a tutorial on creating GUIs for Fortran computational code using Visual Basic.NET. This book is for those who want to learn how to create statistical applications quickly and effectively. Prior experience with a programming language such as Basic, Fortran or C is helpful but not required. More experienced programmers will learn new strategies to harness the power of modern Fortran and the object-oriented paradigm. This may serve as a supplementary text for a graduate course on statistical computing. From the reviews: “This book should be read by all statisticians, engineers, and scientists who want to implement an algorithm as a computer program. The book is the best introduction to programming that I have ever read. I value it as one of my important reference books in my personal library.” Melvin J. Hinich for Techonmetrics, November 2006 “Overall, the book is well written and provides a reasonable introduction to the use of modern versions of Fortran for statistical computation. The real thrust of the book is building COM interfaces using Fortran, and it will no doubt be most useful to anyone who needs to build such interfaces.” Journal of the American Statistical Association, June 2006 “The book is well written and is divided into chapters and sections which are coherent…Overall the book seems like a good resource for someone that already knows some dialect of FORTRAN and wants to learn a bit about what is new in FORTRAN 95…” Robert Gentleman for the Journal of Statistical Software, December 2006.

Developing Statistical Software in Fortran 95 1st Table of contents:

Chapter 1: Introduction to Statistical Software Development
1.1 Overview of Statistical Software
1.2 The Role of Fortran in Scientific Computing
1.3 Objectives and Structure of the Book
1.4 Key Concepts in Software Development
1.5 The Importance of Numerical Precision and Efficiency

Chapter 2: Fortran 95 Programming Basics
2.1 Introduction to Fortran 95
2.2 Syntax and Structure of Fortran Programs
2.3 Data Types and Variables in Fortran
2.4 Control Structures (Loops, Conditionals)
2.5 Functions and Subroutines
2.6 Arrays and Multi-dimensional Data Structures
2.7 I/O Operations in Fortran 95

Chapter 3: Statistical Fundamentals for Software Development
3.1 Descriptive Statistics (Mean, Median, Mode)
3.2 Probability Distributions
3.3 Hypothesis Testing and Confidence Intervals
3.4 Regression Analysis and Correlation
3.5 Sampling Methods and Estimation
3.6 Numerical Methods for Statistics (Integration, Optimization)

Chapter 4: Implementing Basic Statistical Functions in Fortran 95
4.1 Calculating Descriptive Statistics
4.2 Generating Random Numbers and Sampling
4.3 Implementing Probability Distributions
4.4 Hypothesis Testing Functions
4.5 Basic Linear Regression
4.6 Correlation Coefficients and Covariance
4.7 Functions for Statistical Data Transformation

Chapter 5: Advanced Statistical Methods in Fortran 95
5.1 Nonlinear Regression and Curve Fitting
5.2 Time Series Analysis
5.3 Principal Component Analysis (PCA)
5.4 Multivariate Statistics
5.5 Monte Carlo Simulations
5.6 Markov Chain Monte Carlo (MCMC) Methods
5.7 Optimization Algorithms for Statistical Estimation

Chapter 6: Software Design for Statistical Programs
6.1 Modular Programming in Fortran
6.2 Creating Efficient and Reusable Code
6.3 Error Handling and Debugging
6.4 Performance Optimization Techniques
6.5 Memory Management and Data Structures
6.6 Code Documentation and Best Practices
6.7 Unit Testing and Quality Assurance in Statistical Software

Chapter 7: Working with Data
7.1 Reading and Writing Data Files in Fortran
7.2 Handling Large Data Sets Efficiently
7.3 Data Preprocessing and Cleaning Techniques
7.4 Implementing Data Transformation and Normalization
7.5 Visualizing Statistical Results (Integration with External Libraries)

Chapter 8: Integrating Fortran 95 with Other Tools
8.1 Interfacing Fortran with C/C++ Libraries
8.2 Using Fortran with R for Statistical Analysis
8.3 Integration with Python and Other Scripting Languages
8.4 Linking Fortran Programs with External Databases
8.5 Visualizing Statistical Results with External Tools (e.g., MATLAB, Gnuplot)

Chapter 9: Case Studies in Statistical Software Development
9.1 Case Study 1: Statistical Analysis of Experimental Data
9.2 Case Study 2: Implementing a Statistical Model for Forecasting
9.3 Case Study 3: Designing a Statistical Simulation Engine
9.4 Case Study 4: Building a Statistical Web Service
9.5 Lessons Learned from Case Studies

Chapter 10: Advanced Topics in Fortran for Statistical Computing
10.1 Parallel Computing and Multithreading in Fortran
10.2 Using Fortran with GPUs for High-Performance Computing
10.3 Developing Distributed Statistical Software
10.4 Optimizing Computationally Intensive Statistical Methods
10.5 Fortran in Data Science and Machine Learning

Chapter 11: Conclusion and Future Directions
11.1 Recap of Key Concepts in Statistical Software Development
11.2 Trends in Statistical Software Development
11.3 Emerging Technologies in Fortran and Statistical Computing
11.4 The Future of Statistical Software Development
11.5 Final Thoughts and Recommendations

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