DownloadThis 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].
License
GNU Library or Lesser General Public License version 2.0 (LGPLv2)Follow Spectral Analysis Library
You Might Also Like
Deliver a personalized customer experience with every interaction, across every channel, with uContact, net2phone’s cloud contact center solution.
Rate This Project
Login To Rate This Project
User Reviews
Be the first to post a review of Spectral Analysis Library!