Sensitivity Analysis in Practice A Guide to Assessing Scientific Models

Date: 19 January 2011, 08:51

Free register and download UseNet downloader, then you can FREE Download from UseNet.

Download without Limit " Sensitivity Analysis in Practice A Guide to Assessing Scientific Models " from UseNet for FREE!

Sensitivity analysis should be considered a pre-requisite for statistical model building in any scientific discipline where modelling takes place. For a non-expert, choosing the method of analysis for their model is complex, and depends on a number of factors. This book guides the non-expert through their problem in order to enable them to choose and apply the most appropriate method. It offers a review of the state-of-the-art in sensitivity analysis, and is suitable for a wide range of practitioners. It is focussed on the use of SIMLAB Ãƒâ€šÃ‚Â¨C a widely distributed freely-available sensitivity analysis software package developed by the authors Ãƒâ€šÃ‚Â¨C for solving problems in sensitivity analysis of statistical models.
Other key features:
Provides an accessible overview of the current most widely used methods for sensitivity analysis.
Opens with a detailed worked example to explain the motivation behind the book.
Includes a range of examples to help illustrate the concepts discussed.
Focuses on implementation of the methods in the software SIMLAB - a freely-available sensitivity analysis software package developed by the authors.
Contains a large number of references to sources for further reading.
Authored by the leading authorities on sensitivity analysis.

Download Links:

Download Link (High Speed Download)

Download Link (http://www1.vista-server.com/...1126814596.zip)

DISCLAIMER:

This site does not store Sensitivity Analysis in Practice A Guide to Assessing Scientific Models on its server. We only index and link to Sensitivity Analysis in Practice A Guide to Assessing Scientific Models provided by other sites. Please contact the content providers to delete Sensitivity Analysis in Practice A Guide to Assessing Scientific Models if any and email us, we'll remove relevant links or contents immediately.