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Spectral Analysis Library

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Description

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.

Spectral Analysis Library Web Site

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].

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Additional Project Details

Intended Audience

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

Programming Language

Fortran, Python

Registered

2006-05-22

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