Search Results for "multivariate analysis"

The Multivariate Regression Composer, a Matlab toolbox. It generates a regression model of the optimal structure. Uses the source data set, the initial models and the primitive functions.

mTRF-Toolbox is a MATLAB package for modelling multivariate stimulus-response data, suitable for neurophysiological data such as MEG, EEG, sEEG, ECoG and EMG. It can be used to model the functional relationship between neuronal populations and dynamic sensory inputs such as natural scenes and sounds, or build neural decoders for reconstructing stimulus features and developing real-time applications such as brain-computer interfaces (BCIs). Toolbox Paper: ...

...The repository gathers implementations and case studies across many topics commonly used in contest solutions: optimization (linear, integer, goal and nonlinear programming), heuristic and metaheuristic methods (simulated annealing, genetic algorithms, immune algorithms), neural networks and time-series methods, interpolation and regression, graph theory, cellular automata, grey systems, fuzzy models, partial/ordinary differential equations, and multivariate analysis, among others. The codebase is organized into topic folders (e.g., HeuristicAlgorithm, IntegerProgramming, NeuralNetwork, TimeSeries) and includes dozens of worked examples and links to textbook/source materials that the author used to assemble the collection.

The mfBox is a Matlab toolbox for performing model-free analysis of multivariate data sets. It also plugs into SPM used for the analysis of multivariate brain recordings such as fMRI, SPECT and PET data sets. This project is looking for a new maintainer!

LAMBDA is a MatLab toolkit that performs multivariate autoregressive first-order data analysis. LAMBDA estimates community interactions using matrix algebra. The target audience is scientists with long-term ecological data.

MADR is a framework for analysis of series of images (2D data) where each pixel position have the same meaning in every image. Based on a statistical analysis, the images can then be visualised together with parameters from the analysis.