A SAS/JMP Integration for Implementation of a Clustering Algorithm for High Dimensional Low Sample Size Data
نویسنده
چکیده
A SAS macro solution is presented for clustering of high dimensional low sample size (HDLLSS) data using a new algorithm based o p-values as similarity measure. The algorithm PPCLUST was developed by von Borries (2008) and implemented using SAS macro language with the macro autocall facility and window macro command for friendly interface. The SAS interface to JMP was used to run a SAS macro inside JMP and automatically produce graphs using adaptable JMP scripts. An example with partial data from microarray study is presented.
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