Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Bootstrap (1)
- Classification (1)
- Computing (1)
- Cross validation (1)
- Data Analysis (1)
-
- Discrimination (1)
- Emacs Speaks Statistics (1)
- Exploratory analysis (1)
- Genomics (1)
- Grid (1)
- Kriging (1)
- LAM-MPI (1)
- Literate Programming (1)
- MPI (1)
- Message Passing (1)
- Noweb (1)
- PVM (1)
- Prediction (1)
- Profile likelihood (1)
- Programming Tools (1)
- Proteomics (1)
- ROC curves (1)
- Reproducible Research (1)
- Statistical Consulting (1)
- User Interfaces (1)
Articles 1 - 3 of 3
Full-Text Articles in Physical Sciences and Mathematics
Simple Parallel Statistical Computing In R, Anthony Rossini, Luke Tierney, Na Li
Simple Parallel Statistical Computing In R, Anthony Rossini, Luke Tierney, Na Li
UW Biostatistics Working Paper Series
Theoretically, many modern statistical procedures are trivial to parallelize. However, practical deployment of a parallelized implementation which is robust and reliably runs on different computational cluster configurations and environments is far from trivial. We present a framework for the R statistical computing language that provides a simple yet powerful programming interface to a computational cluster. This interface allows the development of R functions that distribute independent computations across the nodes of the computational cluster. The resulting framework allows statisticians to obtain significant speed-ups for some computations at little additional development cost. The particular implementation can be deployed in heterogeneous computing …
Literate Statistical Practice, Anthony Rossini, Friedrich Leisch
Literate Statistical Practice, Anthony Rossini, Friedrich Leisch
UW Biostatistics Working Paper Series
Literate Statistical Practice (LSP, Rossini, 2001) describes an approach for creating self-documenting statistical results. It applies literate programming (Knuth, 1992) and related techniques in a natural fashion to the practice of statistics. In particular, documentation, specification, and descriptions of results are written concurrently with writing and evaluation of statistical programs. We discuss how and where LSP can be integrated into practice and illustrate this with an example derived from an actual statistical consulting project. The approach is simplified through the use of a comprehensive, open source toolset incorporating Noweb, Emacs Speaks Statistics (ESS), Sweave (Ramsey, 1994; Rossini, et al, 2002; …
Selecting Differentially Expressed Genes From Microarray Experiments, Margaret S. Pepe, Gary M. Longton, Garnet L. Anderson, Michel Schummer
Selecting Differentially Expressed Genes From Microarray Experiments, Margaret S. Pepe, Gary M. Longton, Garnet L. Anderson, Michel Schummer
UW Biostatistics Working Paper Series
High throughput technologies, such as gene expression arrays and protein mass spectrometry, allow one to simultaneously evaluate thousands of potential biomarkers that distinguish different tissue types. Of particular interest here is cancer versus normal organ tissues. We consider statistical methods to rank genes (or proteins) in regards to differential expression between tissues. Various statistical measures are considered and we argue that two measures related to the Receiver Operating Characteristic Curve are particularly suitable for this purpose. We also propose that sampling variability in the gene rankings be quantified and suggest using the “selection probability function”, the probability distribution of rankings …