Showing 10 open source projects for "testing"

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  • 1
    MarketData.jl

    MarketData.jl

    Time series market data

    The MarketData package provides open-source financial data for research and testing. The data is from Quandl and is free end-of-day stock data. It is public domain without restrictions. The TimeSeries TimeArray data structure is used to store the data, but conversion to other data structures, including DataFrames and AxisArrays, is supported.
    Downloads: 0 This Week
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  • 2
    CausalityTools.jl

    CausalityTools.jl

    Algorithms for detecting associations, dynamical influences

    ...For example, we offer the generic SurrogateTest, which is fully compatible with TimeseriesSurrogates.jl, and the LocalPermutationTest for conditional independence testing.
    Downloads: 0 This Week
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  • 3
    ReTest.jl

    ReTest.jl

    Testing framework for Julia

    ReTest is a testing framework for Julia allowing defining tests in source files, whose execution is deferred and triggered on demand. This is useful when one likes to have definitions of methods and corresponding tests close to each other. This is also useful for code that is not (yet) organized as a package, and where one doesn't want to maintain a separate set of files for tests.
    Downloads: 0 This Week
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  • 4
    LinearSolve.jl

    LinearSolve.jl

    High-Performance Unified Interface for Linear Solvers in Julia

    LinearSolve.jl is a unified interface for the linear solving packages of Julia. It interfaces with other packages of the Julia ecosystem to make it easy to test alternative solver packages and pass small types to control algorithm swapping. It also interfaces with the ModelingToolkit.jl world of symbolic modeling to allow for automatically generating high-performance code. Performance is key: the current methods are made to be highly performant on scalar and statically sized small problems,...
    Downloads: 12 This Week
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  • 5
    The ARCHModels Package for Julia

    The ARCHModels Package for Julia

    A Julia package for estimating ARMA-GARCH models

    ARCH (Autoregressive Conditional Heteroskedasticity) models are a class of models designed to capture a feature of financial returns data known as volatility clustering, i.e., the fact that large (in absolute value) returns tend to cluster together, such as during periods of financial turmoil, which then alternate with relatively calmer periods. This package provides efficient routines for simulating, estimating, and testing a variety of GARCH models. ARCH (Autoregressive Conditional Heteroskedasticity) models are a class of models designed to capture a feature of financial returns data known as volatility clustering, i.e., the fact that large (in absolute value) returns tend to cluster together, such as during periods of financial turmoil, which then alternate with relatively calmer periods.
    Downloads: 0 This Week
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  • 6
    Bayesian Statistics

    Bayesian Statistics

    This repository holds slides and code for a full Bayesian statistics

    ...Bayesian statistics is a departure from classical inferential statistics that prohibits probability statements about parameters and is based on asymptotically sampling infinite samples from a theoretical population and finding parameter values that maximize the likelihood function. Mostly notorious is null-hypothesis significance testing (NHST) based on p-values.
    Downloads: 0 This Week
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  • 7
    Bayesian Julia

    Bayesian Julia

    Bayesian Statistics using Julia and Turing

    ...Bayesian statistics is a departure from classical inferential statistics that prohibits probability statements about parameters and is based on asymptotically sampling infinite samples from a theoretical population and finding parameter values that maximize the likelihood function. Mostly notorious is null-hypothesis significance testing (NHST) based on p-values. Bayesian statistics incorporate uncertainty (and prior knowledge) by allowing probability statements about parameters.
    Downloads: 3 This Week
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  • 8
    MonteCarlo.jl

    MonteCarlo.jl

    Classical and quantum Monte Carlo simulations in Julia

    ...Note that classical Monte Carlo is also not a focus at this point. It is probably usable, but a lot of the adjustments made to DQMC have not been added to classical Monte Carlo, or have been added without thorough testing.
    Downloads: 0 This Week
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  • 9
    Strategems

    Strategems

    Quantitative systematic trading strategy development and backtesting

    Strategems is a Julia package aimed at simplifying and streamlining the process of developing, testing, and optimizing algorithmic/systematic trading strategies. This package is inspired in large part by the quantstrat1,2 package in R, adopting a similar general structure to the building blocks that make up a strategy. Given the highly iterative nature of event-driven trading strategy development, Julia's high-performance design (particularly in the context of loops) and straightforward syntax would seem to make it a natural fit as a language for systematic strategy research and development. ...
    Downloads: 0 This Week
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  • 10
    Immerse.jl

    Immerse.jl

    Dive deeper into your data with interactive graphics

    Dive deeper into your data with interactive graphics. Immerse is a wrapper that adds graphical interactivity to Julia's plots. Currently, Immerse supports Gadfly. The toolbar at the top supports saving your figure to a file, zooming and panning, and lasso selection. Zooming and panning uses the defaults set by GtkUtilities. The left mouse button allows you to rubberband-select a zoom region. Use your mouse wheel or arrow-keys to pan or change the zoom level. Double-click, or press the 1:1...
    Downloads: 0 This Week
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