Developing Statistical Software in Fortran 95 Statistics and Computing

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

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.

David R. Lemmon is a Research Associate at The Methodology Center in The Pennsylvania State University's College of Health and Human Development. He holds a Ph.D. in Mechanical Engineering from the University of Cincinnati. His areas of previous work include finite element analysis, automobile crash simulation, and biomechanical modeling of the diabetic foot. Since 2001, he has served as the Center's Senior Statistical Programmer, managing the creation of new statistical software for research and education.

Joseph L. Schafer is Associate Professor in the Department of Statistics at The Pennsylvania State University and a Principal Investigator at The Methodology Center. He holds a Ph.D. in Statistics from Harvard University. His areas of research include statistical methods for missing values, analysis of longitudinal data, statistical computing and methodology for studies of substance-use prevention. He has served as a statistical consultant to numerous government agencies and has taught many workshops and short courses on topics related to missing data.