| 1 | # -*- coding: utf-8; mode: tcl; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- vim:fenc=utf-8:ft=tcl:et:sw=4:ts=4:sts=4 |
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| 2 | # $Id$ |
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| 3 | |
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| 4 | PortSystem 1.0 |
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| 5 | PortGroup python 1.0 |
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| 6 | |
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| 7 | name EGSimulation |
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| 8 | version 1.0 |
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| 9 | categories science |
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| 10 | |
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| 11 | license public-domain |
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| 12 | supported_archs noarch |
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| 13 | description Simulate the Ellison & Glaeser statistic using randomness alone |
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| 14 | maintainers ad.wsu.edu:tazz_ben |
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| 15 | |
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| 16 | long_description By using a simulation of firm sizes (using a lognormal distribution) and specified geographic regions, standard deviations and employee head count, we can compute the critical regions for the Ellison & Glaeser statistic. In the process, it also calculates herfindahl values and provides critical regions. |
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| 17 | |
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| 18 | homepage https://github.com/tazzben/EconScripts/tree/master/Simulations/Python/EG%20Statistic |
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| 19 | master_sites https://github.com/downloads/tazzben/EconScripts/ |
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| 20 | |
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| 21 | checksums rmd160 5dcd5d51188a9fa6e550383fbc57bf655119a0ed \ |
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| 22 | sha256 2a3fcdbacee642ef701561ea6664208a427f453a09bc39be0a28710d1a6dbff4 |
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| 23 | |
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| 24 | python.versions 26 27 |
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| 25 | python.default_version 27 |
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| 26 | |
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| 27 | depends_lib-append port:py${python.version}-crypto port:py${python.version}-numpy port:py${python.version}-scipy |
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| 28 | |
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| 29 | python.link_binaries_suffix |
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