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Bioinformatics. 2008 Sep 1;24(17):1966-7. doi: 10.1093/bioinformatics/btn329. Epub 2008 Jul 17.

mlegp: statistical analysis for computer models of biological systems using R.

Author information

1
Program in Bioinformatics & Computational Biology, Department of Statistics and Department of Genetics, Development & Cell Biology, Iowa State University, Ames, IA 50010, USA.

Abstract

Gaussian processes (GPs) are flexible statistical models commonly used for predicting output from complex computer codes. As such, GPs are well suited for the analysis of computer models of biological systems, which have been traditionally difficult to analyze due to their high-dimensional, non-linear and resource-intensive nature. We describe an R package, mlegp, that fits GPs to computer model outputs and performs sensitivity analysis to identify and characterize the effects of important model inputs.

AVAILABILITY:

http://www.biomath.org/mlegp

PMID:
18635570
PMCID:
PMC2732217
DOI:
10.1093/bioinformatics/btn329
[Indexed for MEDLINE]
Free PMC Article

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