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Showing 8 open source projects for "find"
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1
Statistics
Detects usage of unsafe Rust in a Rust crate and its dependencies
A tool that lists statistics related to the usage of unsafe Rust code in a Rust crate and all its dependencies. -
2
GIT quick statistics
An efficient way to access various statistics in git repository
git-quick-stats is a simple and efficient way to access various statistics in a git repository. Any git repository may contain tons of information about commits, contributors, and files. Extracting this information is not always trivial, mostly because there are a gadzillion options to a gadzillion git commands. For those who prefer to utilize command-line options, git-quick-stats also has a non-interactive mode supporting both short and long options. You can change to the legacy color... -
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MCPower
MCPower — simple Monte Carlo power analysis for complex models
...It guides users through the full workflow across three tabs: Model setup (formula input with live parsing, CSV data upload with auto-detected variable types, effect size sliders, and correlation editing), Analysis configuration (find power for a given sample size or find the minimum sample size for a target power, with multiple testing correction and scenario analysis), and Results (interactive charts, exportable tables, and auto-generated Python replication scripts). Supports both standard linear models and mixed-effects models. Additional features include analysis history, configurable scenarios, and built-in documentation. -
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Statistics101 - Resampling Statistics
Use simulation to perform statistical analyses.
...Julian Simon (https://www.juliansimon.com/) and Peter Bruce (https://www.scientificamerican.com/author/peter-bruce/) as a new way to teach Statistics to social science students. Of course, social science students aren't the only ones who can benefit. Anyone who wants to learn statistics will find that the resampling approach helps in understanding statistical concepts from the simplest to the most difficult. In addition, professionals who want to use resampling, bootstrapping, or Monte Carlo simulations will find Statistics101 helpful. More information at https://statistics101.sourceforge.io/ -
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5
gsasnp2
PubMed ID: 29562348 / DOI: 10.1093/nar/gky175
... * PubMed ID: 29562348 * DOI: 10.1093/nar/gky175 -> PLEASE MOVE OR MAKE A COPY OF 'DATA' FOLDER INTO YOUR INTENSIVE TEST FOLDER (I.E. LINUX, MAC OR WINDOWS SPECIFIED FOLDER) TO ALLOW THE PROGRAM TO FIND THE PREDESIGNED DATA. * UPDATE NOTE: -> Sep-1-2020: add an update for Ubuntu-20.04. You will need Boost library installed (sudo apt-get install libboost-all-dev) -> Mar-7-2018: revise header terms in the output file -
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LQFB-analyser
A lqfb delegation analyser. A 3d directed weighted multi graph.
A rich client to analyse data from a liquid-feedback (http://liquidfeedback.org/) instance, for now it's a 3d graph explorer to inspect the delegations. It's an application based on the eclipse platform (indigo). To be precise its a directed weighted multi graph browser in 3d. Find out more in the wiki https://sourceforge.net/p/lqfbanalyser/wiki/Home/ . Generated reports https://sourceforge.net/p/lqfbanalyser/wiki/generated%20lqfb%20reports/ . -
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EnvStats
An R Package for Environmental Statistics
...EnvStats brings the major environmental statistical methods found in the literature and regulatory guidance documents into one statistical package, along with an extensive hypertext help system that explains what these methods do, how to use these methods, and where to find them in the environmental statistics literature. Also included are numerous built-in data sets from regulatory guidance documents and the environmental statistics literature. EnvStats combined with other R packages (e.g., for spatial analysis) provides the environmental scientist, statistician, researcher, and technician with tools to “get the job done!” -
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segment
Solve the Viterbi algorithm in a data stream
It is often necessary to assign a series of discrete values to continuosly variable data sequenced by time, position, etc., thereby parsing the data into fewer and larger segments of variable width. The 'segment' utility takes an input data stream as a Hidden Markov Model and applies the Viterbi algorithm to find the most likely segmentation path through the data.
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