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* BUG: Return correct output for invgauss.cdf when mu is very small

* Update scipy/stats/_continuous_distns.py

Co-authored-by: Matt Haberland <mhaberla@calpoly.edu>

* Update scipy/stats/_continuous_distns.py

Co-authored-by: Matt Haberland <mhaberla@calpoly.edu>

* ENH: Implement logsf and logcdf for invgauss

* MAINT: stats: implement wald sf/logcdf/logsf

* rewrite logcdf & losf expressions to account for small very small x

* TST: add test cases for invgauss cdf, logcdf and logsf

* TST: stats: strengthen tests of invgauss improvements

Co-authored-by: Matt Haberland <mhaberla@calpoly.edu>
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README.rst

SciPy

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SciPy (pronounced "Sigh Pie") is open-source software for mathematics, science, and engineering. It includes modules for statistics, optimization, integration, linear algebra, Fourier transforms, signal and image processing, ODE solvers, and more.

SciPy depends on NumPy, which provides convenient and fast N-dimensional array manipulation. SciPy is built to work with NumPy arrays, and provides many user-friendly and efficient numerical routines, such as routines for numerical integration and optimization. Together, they run on all popular operating systems, are quick to install, and are free of charge. NumPy and SciPy are easy to use, but powerful enough to be depended upon by some of the world's leading scientists and engineers. If you need to manipulate numbers on a computer and display or publish the results, give SciPy a try!

For the installation instructions, see INSTALL.rst.txt.

We appreciate and welcome contributions. If you would like to take part in SciPy development, take a look at the file CONTRIBUTING.rst.