| 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 |
|---|
| 2 | # $Id$ |
|---|
| 3 | |
|---|
| 4 | PortSystem 1.0 |
|---|
| 5 | PortGroup python 1.0 |
|---|
| 6 | |
|---|
| 7 | name EGSimulation |
|---|
| 8 | version 1.0 |
|---|
| 9 | categories science |
|---|
| 10 | |
|---|
| 11 | license Public Domain |
|---|
| 12 | supported_archs noarch |
|---|
| 13 | description Simulate the Ellison & Glaeser statistic using randomness alone |
|---|
| 14 | maintainers ad.wsu.edu:tazz_ben |
|---|
| 15 | |
|---|
| 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. |
|---|
| 17 | |
|---|
| 18 | extract.mkdir no |
|---|
| 19 | homepage https://github.com/tazzben/EconScripts/tree/master/Simulations/Python/EG%20Statistic |
|---|
| 20 | master_sites https://github.com/downloads/tazzben/EconScripts/ |
|---|
| 21 | |
|---|
| 22 | depends_lib port:py27-crypto port:py27-numpy port:py27-scipy |
|---|
| 23 | |
|---|
| 24 | checksums rmd160 5dcd5d51188a9fa6e550383fbc57bf655119a0ed \ |
|---|
| 25 | sha256 2a3fcdbacee642ef701561ea6664208a427f453a09bc39be0a28710d1a6dbff4 |
|---|
| 26 | |
|---|
| 27 | python.default_version 27 |
|---|
| 28 | python.version 27 |
|---|
| 29 | |
|---|
| 30 | python.link_binaries_suffix |
|---|
