Showing 46 open source projects for "command-line kill linux"

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  • 1

    datadensityplot

    Creates a data density plot of a 2 dimensional data distribution.

    Shows the data density of a 2 dimensional distribution. The problem of showing data density visually is not mathematically well defined, and there are several methods. The program uses sum of reciprocal squared distance to calculate density at each point, with a smear factor to prevent points going to infinity. The smear factor also controls the amount of clustering. There are several options for colour output. Input is via a csv (comma-separated values) file. Now there's a nice GUI...
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  • 2
    fesslix

    fesslix

    Stochastic Analysis

    A brief summary of the main features of Fesslix: - Perform non-intrusive reliability analysis or Bayesian updating either --- by running commands on the command line or --- by means of an Octave interface or --- by means of a Python interface - Flexible input language for writing Fesslix parameter files --- Control flow statements (e.g. if, for, while) --- Most parameters can be defined as functions - Working with response surfaces - Linear finite element analysis using truss, beam...
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  • 3
    Statistics modules in Perl Data Language, with a quick-start guide for non-PDL people. They make the PDL shell work like R, but with PDL threading (fast automatic iteration) of procedures including t-test, linear regression, and k-means clustering.
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  • 4
    A collection of small utilities with a connection to cryptography and cryptanalysis. Written for efficiency and a small memory footprint.
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  • 5

    abc-sde

    approximate Bayesian computation for stochastic differential equations

    A MATLAB toolbox for approximate Bayesian computation (ABC) in stochastic differential equation models. It performs approximate Bayesian computation for stochastic models having latent dynamics defined by stochastic differential equations (SDEs) and not limited to the "state-space" modelling framework. Both one- and multi-dimensional SDE systems are supported and partially observed systems are easily accommodated. Variance components for the "measurement error" affecting the...
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  • 6

    libfgen

    Library for optimization using a genetic algorithm or particle swarms

    libfgen is a library that implements an efficient and customizable genetic algorithm (GA). It also provides particle swarm optimization (PSO) functionality and an interface for real-valued function minimization or model fitting. It is written in C, but can also be compiled with a C++ compiler. Both Linux and Windows are supported.
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  • 7
    R packages supporting parallel computing.
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  • 8
    Nen

    Nen

    neural network implementation in java

    3-layer neural network for regression and classification with sigmoid activation function and command line interface similar to LibSVM. Quick Start: "java -jar nen.jar"
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  • 9

    knowceans

    Utility classes from maps to search engine to random samplers

    Collection of several multi-purpose Java libraries. --- knowceans-tools = collection of Java utility classes. --- Highlights: --- org.knowceans.util: IndexQuickSort, TableList: apply order of one array/list to others +++ Vectors, ArrayUtils: array convenience +++ RandomSamplers, CokusRandom, ArmSampler, Densities: random sampling and distributions +++ Arguments: command line parser +++ StopWatch, Which, ExternalProcess: runtime stuff +++ ParallelFor: OpenMP workalike +++ PatternString,...
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  • 10
    This software computes likelihoods for infinitely-many-sites sequence data under multiple merger coalescents. The likelihood can be computed exactly or approximated via importance sampling.
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  • 11
    A collection of compact, powerful programs and functions, written in C, for the analysis and transformation of data. No object or structure dependencies, no fancy interfaces - just good tools.
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  • 12
    clusterCons
    An R package implementation of a consensus clustering methodology. This package allows users to perform re-sampling statistics based clustering using multiple clustering algorithms to assess the robustness of both clusters and members of clusters.
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  • 13
    This project hosts tools used for analysis of Gaussian Mixture Distributions (GMDs) which are used for statistical signal processing. The tools are libraries for implementing GMD operations and programs used to analyze properties of GMDs.
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  • 14
    Worst Cases is a python script that enables calculations on worst case objects. Like a calculator operating on worst cases (e.g. [1,2,3]) rather than on real numbers (2.35) WARNING: This program is released as is, and has never been extensively teste
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  • 15
    LCMStats - An R package
    An R package for detailed inspection and analysis of LCMS data. An R package developed by Sukhdeep Singh at Department of Surgery and Cancer, Imperial College London,UK.
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  • 16
    Stand-alone software tool for the interactive CE analysis of microarray data. The software is a user-friendly and allows on-the-fly study of CE
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  • 17
    Software made available by the Residual Analysis blog, primarily having to do with anthropogenic global warming, e.g. GHCN Processor.
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  • 18
    Provides an API, which enables the Matlab or Octave user (and developer) to incorporate Space Weather data and metadata resources from the Space Physics Interactive Data Resource (SPIDR) directly into an Matlab/Octave application. Examples included.
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  • 19
    Provides an API, which enables the Interactive Data Language (IDL) user (and developer) to incorporate Space Weather data and metadata resources from the Space Physics Interactive Data Resource (SPIDR) directly into an IDL application. Examples included.
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  • 20
    Python module to track the overall median of a stream of values "on-line" in reasonably efficient fashion.
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  • 21
    A MATLAB package to simulate sample paths of the solution of a Itô or Stratonovich stochastic differential equation (SDE), compute statistics and estimate the parameters from data. A note of caution: SDE Toolbox is no more developed but it's still downloadable. Its inferential capabilities can be considered surpassed (at best). Actually the parameter estimation methods were already far from the state-of-art when the project began in 2007 (!). The considered implemented parametric and...
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