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In particular, we provide a submodule `fastcan.narx` to build Nonlinear AutoRegressive eXogenous (NARX) models.
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For more information, check our `Home Page <https://fastcan.readthedocs.io/en/latest/>`_.
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Support Free-Threaded Wheels
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----------------------------
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FastCan has support for free-threaded (also known as nogil) CPython 3.13.
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fastcan has support for free-threaded (also known as nogil) CPython 3.13.
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For more information about free-threaded CPython, check `how to install a free-threaded CPython <https://py-free-threading.github.io/installing_cpython/>`_.
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Support WASM Wheels
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-------------------
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FastCan is compiled to WebAssembly (WASM) wheels using `pyodide <https://github.com/pyodide/pyodide>`_, and they are available on the assets of GitHub releases.
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fastcan is compiled to WebAssembly (WASM) wheels using `pyodide <https://github.com/pyodide/pyodide>`_, and they are available on the assets of GitHub releases.
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You can try it in a `REPL <https://pyodide.org/en/stable/console.html>`_ directly in a browser.
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The WASM wheels of FastCan can be installed by
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The WASM wheels of fastcan can be installed by
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>>> import micropip # doctest: +SKIP
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>>> await micropip.install('URL of the wasm wheel (end with _wasm32.whl)') # doctest: +SKIP
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📝 **Note:** Due to the Cross-Origin Resource Sharing (CORS) block in web browsers,
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you may need `Allow CORS: Access-Control-Allow-Origin Chrome extension <https://chrome.google.com/webstore/detail/allow-cors-access-control/lhobafahddgcelffkeicbaginigeejlf>`_.
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📝 **Note:** The nightly wasm wheel of FastCan's dependency (i.e. scikit-learn) can be found in `Scientific Python Nightly Wheels <https://pypi.anaconda.org/scientific-python-nightly-wheels/simple/>`_.
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📝 **Note:** The nightly wasm wheel of fastcan's dependency (i.e. scikit-learn) can be found in `Scientific Python Nightly Wheels <https://pypi.anaconda.org/scientific-python-nightly-wheels/simple/>`_.
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Citation
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--------
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FastCan is a Python implementation of the following papers.
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fastcan is a Python implementation of the following papers.
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If you use the `h-correlation` method in your work please cite the following reference:
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