• CRAN

  • Referenced in 570 articles [sw04351]
  • linear and nonlinear modelling, statistical tests, time series analysis, classification, clustering, etc. Please consult ... homepage for further information. CRAN is a network of ftp and web servers around...
  • ANFIS

  • Referenced in 285 articles [sw08730]
  • system implemented in the framework of adaptive networks. By using a hybrid learning procedure ... chaotic time series, all yielding remarkable results. Comparisons with artificial neural networks and earlier work...
  • Neural Network Toolbox

  • Referenced in 178 articles [sw07378]
  • Neural Network Toolbox for applications such as data fitting, pattern recognition, clustering, time-series prediction...
  • pyunicorn

  • Referenced in 8 articles [sw19314]
  • Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package ... modeling from complex network theory and nonlinear time series analysis. exttt{pyunicorn} is a fully ... spatial networks, networks of interacting networks, node-weighted statistics or network surrogates. Additionally, pyunicorn provides ... analysis (RQA), recurrence networks, visibility graphs and construction of surrogate time series. The range...
  • ScaLAPACK

  • Referenced in 421 articles [sw00830]
  • distributed memory message-passing MIMD computers and networks of workstations supporting parallel virtual machine ... Cray T3, IBM SP, Intel series, TM CM-5, clusters of workstations, and any system ... source code for the package, testing and timing programs, prebuilt version of the library...
  • REVEAL

  • Referenced in 29 articles [sw36999]
  • genetic networks. Trajectories, or state transition tables of Boolean nets, resemble time series of gene ... controlling each element or gene in the network. This process is unequivocal and exact...
  • GNAR

  • Referenced in 3 articles [sw31350]
  • package GNAR: Methods for Fitting Network Time Series Models. Simulation of, and fitting models ... Generalised Network Autoregressive (GNAR) time series models which take account of network structure. Such models...
  • Pypsa

  • Referenced in 9 articles [sw21552]
  • scale well with large networks and long time series...
  • Linda

  • Referenced in 103 articles [sw09427]
  • distributed settings generally and on integrated network computers in particular. It differs from previous interprocess ... fully distributed in space and distributed in time; it allows distributed sharing, continuation passing ... properties and their implications, then give a series of examples. Linda presents novel implementation problems...
  • ordpy

  • Referenced in 3 articles [sw37285]
  • essential tool for time series analysis. Beyond becoming a popular and successful technique, permutation entropy ... inspired a framework for mapping time series into symbolic sequences that triggered the development ... including an approach for creating networks from time series known as ordinal networks. Despite ... patterns, ordinal networks, and missing ordinal transitions for one-dimensional (time series) and two-dimensional...
  • rocket

  • Referenced in 5 articles [sw38157]
  • random convolutional kernels. Most methods for time series classification that attain state ... have high computational complexity, requiring significant training time even for smaller datasets, and are intractable ... recent success of convolutional neural networks for time series classification, we show that simple linear...
  • fabisearch

  • Referenced in 2 articles [sw38226]
  • Change Point Detection in High-Dimensional Time Series Networks. Implementation of the Factorized Binary Search ... network (or clustering) structure of multivariate high-dimensional time series. The method is motivated ... est.net(), for estimating a network between stationary multivariate time series, net.3dplot(), for plotting the estimated ... tested on simulated multivariate high-dimensional time series data and fMRI data. For details...
  • RLDDE

  • Referenced in 3 articles [sw35866]
  • delay estimator for neural networks in time series prediction. Time series prediction is traditionally handled ... linearity in the data. Neural networks are non-linear models that are suitable to handle ... linearity in time series. When designing a neural network for prediction, two critical factors that ... affect the performance of the neural network predictor should be considered; they are namely...
  • GeneNet

  • Referenced in 9 articles [sw07992]
  • Inferring Gene Networks. GeneNet is a package for analyzing gene expression (time series) data with...
  • SSE

  • Referenced in 3 articles [sw15703]
  • analysis of university e-learning network traffic to work out and validate the methods that ... line monitoring of self-similarity. Time series of network traffic analyzed are formed by registering...
  • DeepAR

  • Referenced in 6 articles [sw38790]
  • Recurrent Networks. Probabilistic forecasting, i.e. estimating the probability distribution of a time series’ future given ... right inventory available at the right time at the right place. In this paper ... regressive recurrent network model on a large number of related time series. We demonstrate...
  • psychonetrics

  • Referenced in 3 articles [sw34796]
  • Psychometric network models from time-series and panel data. Researchers in the field of network ... Gaussian graphical models (GGMs) -- an undirected network model of partial correlations -- between observed variables ... cross-sectional data or single-subject time-series data. This assumes that all variables...
  • EDISON

  • Referenced in 2 articles [sw08266]
  • MCMC simulation to reconstruct networks from time series data, using a non-homogeneous, time-varying...
  • NetOnZeroDXC

  • Referenced in 1 article [sw39857]
  • identification of networks out of multivariate time series via zero-delay cross-correlation. The identification ... links between nodes of a network by analyzing time series associated to those nodes ... assessment of networks out of multivariate time series. The method relies on the computation ... delay cross-correlation between pairs of time series. The software implements the various stages...
  • GENeVis

  • Referenced in 2 articles [sw06743]
  • visualization of gene regulatory networks with associated gene expression time series data We present GENeVis ... visualize gene expression time series data in a gene regulatory network context. This ... attribute, multiple time point visualization, and visual comparison of multiple time series in one view ... case study, in which gene expression time series data acquired in-house are analyzed...