This project provides a Fortran90 library and a python module for singular spectrum analyses such as PCA/EOF or MSSA. It is intended for people interested, for example, in analysing climate or financial variability.

Features

  • PCA for extracting dominant spatial pattern of variability.
  • SSA/MSSA which is like PCA but for extracting spatio-temporal patterns.
  • Joined SVD which is like PCA but for extracting the common variability of two variables (using cross-covariances).
  • SVD model deduce a predictand from a predictor using SVD.
  • Full missing value support.
  • Switch of space and time for PCA analyses performed on a large number of channels.
  • For analysis, empirical orthogonal functions (EOFs), principal componants (PCs), expansion coefficient (ECs) and reconstructions of signal are available.
  • Analyses can be performed on several variables at the same time, with normalisation coefficents [python].
  • Pre-PCA analysis to reduct the d-o-f before analysing huge datasets with MSSA or SVD.
  • Monte-Carlo test for (M)SSA (MC-SSA) [python].
  • Full UV-CDAT support [python].

Project Activity

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License

GNU Library or Lesser General Public License version 2.0 (LGPLv2)

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Additional Project Details

Operating Systems

Linux, BSD

Intended Audience

Financial and Insurance Industry, Science/Research, Advanced End Users, Developers

Programming Language

Fortran, Python

Related Categories

Fortran Financial Software, Fortran Mathematics Software, Fortran Earth Sciences Software, Python Financial Software, Python Mathematics Software, Python Earth Sciences Software

Registered

2006-05-22