Search Results for "python time series analysis"
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Showing 25 open source projects for "python time series analysis"
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CausalImpact
An R package for causal inference in time series
The CausalImpact repository houses an R package that implements causal inference in time series using Bayesian structural time series models. Its goal is to estimate the effect of an intervention (e.g. a marketing campaign, policy change) on a time series outcome by predicting what would have happened in a counterfactual “no intervention” world. The package requires as input a response time series plus one or more control (covariate) time series that are assumed unaffected by the... -
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AtteStat
The package for statistical data analysis and applied mathematics
Less means - more power. The high performance open source package for statistical data analysis and applied mathematics AtteStat is an add-in for desktop versions of the Microsoft Excel spreadsheets. Both 32-bit and 64-bit in one package. Winner of contest Microsoft Office Extensions (PC Magazine RE) in 2006. Registered 2002-05-23 with the Federal Service for Intellectual Property. Completely free. No donation required. AtteStat comes with absolutely no warranty. The software is not... -
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Book-Reviews-In-Mathematica
Partial Differential Equations, Complex Analysis, Mathematica, Farlow
Cliff* Notes, Mathematica Evaluatable "Partial Differential Equations for Scientists and Engineers", Farlow "Physics for Scientists and Engineers", Serway "A First Course in Complex Analysis", Beck "PDE", Asmar "PDE, An Introduction", Colton "Elementary Differential Equations", 7th, Rainville "Ordinary Differential Equations", Tenenbaum "Linear Algebra And It's Applications", Lay "Swokowski Calculus", 5th, Swokowski "Chemistry Concepts & Problems, A Self-Teaching Guide",... -
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Algorithms Math Models
MATLAB implementations of algorithms
...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. -
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Geophysical Library is a C++-library to handle geophysical data. At the moment the focus is on magnetotelluric and seismic data. It also includes a genetic algorithm for data inversion, signal processing and statistics routines.
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PlanetPack
Radial-velocity & transits analysis tool for exoplanets
PlanetPack is a software tool developed to facilitate the radial-velocity time-series analysis for the goal of exoplanets detection, characterization, and basic dynamical simulations. The description of the main theoretic concepts, statistical methods and algorithms that PlanetPack implements, is given in the following refereed papers: R.V. Baluev 2013, Astronomy & Computing, V. 2, P. 18 (initial release); R.V. -
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Tsf_Mdnnhn
Time Series Forecasting.
Implementation of algorithm allowing Time Series Forecasting. -
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All future developments will be implemented in the new MATLAB toolbox SciXMiner, please visit https://sourceforge.net/projects/scixminer/ to download the newest version. The former Matlab toolbox Gait-CAD was designed for the visualization and analysis of time series and features with a special focus to data mining problems including classification, regression, and clustering.
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LDT
Automatic Time Series Analysis with Stationary VAR Models
LDT is designed for automatic time-series analysis. Current version focuses on stationary vector autoregressive models (VAR) and the related analyses such as forecasting and Granger causality. See the following paper for an application: See http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2818213 -
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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.
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ctsa
A Univariate Time Series Analysis package in ANSI C
CTSA is a C software package for univariate time series analysis. This is a work in progress. ARIMA and Seasonal ARIMA models have been added so far. Other functionality will be added soon . Documentation - https://github.com/rafat/ctsa/wiki -
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wmtsa-python
Discrete wavelet methods for time series analysis using python
Several python libraries implement discrete wavelet transforms. However, none of them, or at least none that I know, is aimed at scientific use. This library aims at filling this gap, in particular considering discrete wavelet transform as described by Percival and Walden. This module started as translation of the wmtsa Matlab toolbox (http://www.atmos.washington.edu/~wmtsa/), so most naming conventions and most of the code structure follows their choices. The code uses a mix of python and... -
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TIDES
Taylor series Integrator for Differential Equations
Taylor series Integrator for Differential EquationS. This software is developed by Profs. A. Abad, R. Barrio, F. Blesa and M. Rodriguez, (GME, University of Zaragoza, Spain). It consists on a C (Fortran) library, libTIDES, and a Mathematica package, MathTIDES. (MathTIDES requires Mathematica version >= 7.0) . Basic references: * A. Abad, R. Barrio, F. Blesa, M. Rodriguez, 2012. Algorithm 924: TIDES, a Taylor series Integrator for Differential EquationS, ACM TOMS. 39, no. 1, art. 5.... -
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DeDAY
MLE survival analysis: Gompertz, Weibull, Logistic and mixed morality.
DeDAY (Demography Data Analyses) is a tool of analyzing demography data. It supports Gompertz, Weibull and Logistic distributions. DeDay also supports mixed mortality models based on these distribution such as the Gompertz-Makeham distribution. Distributions such as Gompertz describes only age-dependent mortality, which increases over time. Mixed mortality models, such as in Gompertz-Makeham distribution, consider a more general case where mortality is consist of both age-dependent and... -
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Statistical models with python using numpy and scipy. Currently covers linear regression (with ordinary, generalized and weighted least squares), robust linear regression, and generalized linear model, discrete models, time series analysis and other statistical methods.
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Tidal Analysis Program in PYthon (TAPPY) uses the least squares optimization function from scipy to perform a harmonic analysis (calculate amplitude and phases of a set of sine waves) of a hourly time series of water level values.
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A MATLAB toolbox for time series analysis using state space models. Supports fully interactive model construction with MATLAB objects and efficient Kalman filter backend implemented in c.
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ptsa (pronounced pizza) stands for Python Time Series Analysis. A python module specifically designed with neural data in mind (EEG, MEG, fMRI, etc...), but applicable to almost any type of time series.
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JMulTi is an interactive software designed for univariate and multivariate time series analysis. It has a Java graphical user interface that uses an external engine for statistical computations. It uses the framework JStatCom.
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To develop a software package for time series manipulation and cycles analysis. Cycles means repeated occurrences at nearly equal time intervals in any time series data. See http://www.cyclesresearchinstitute.org/ for a site about cycles.
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SciGraphica is a scientific data visualization and analysis application, supplying many of the basic plotting features for 2D and 3D charts. It features opening several worksheets and plots to work with at the same time and PS output.
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JTSA is an educational time series analysis tool for simple calculations and forecasts using the additional or multiplicative seasonal decomposition method.
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Real-time data visualization. Graphically view your data as it's being generated. Peakster is a very intuitive GUI written entirely in Python, which monitors data at regular intervals and uses gnuplot to render 2D, 3D and superimposed plots.
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Data Mining Platform is a platform for data mining and analysis. It contains many of the new and sophisticated methods such as kernel-based classification, two-way clustering, bayesian networks, pattern recognition for time series analysis and many other
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