{ "info": { "author": "Bryan S. Graham", "author_email": "bgraham@econ.berkeley.edu", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha", "Intended Audience :: Science/Research", "License :: OSI Approved :: MIT License", "Programming Language :: Python :: 2.7", "Topic :: Scientific/Engineering :: Mathematics" ], "description": "netrics: a Python 2.7 package for econometric analysis of networks\n-----------------------------------------------------------------------------\nby Bryan S. Graham, UC - Berkeley, e-mail: bgraham@econ.berkeley.edu\n\n\nThis package includes a Python 2.7 implementation of the two econometric\nnetwork formation models introduced in Graham (2014, NBER).\n\nThis package is offered \"as is\", without warranty, implicit or otherwise. While I would\nappreciate bug reports, suggestions for improvements and so on, I am unable to provide any\nmeaningful user-support. Please e-mail me at bgraham@econ.berkeley.edu\n\nPlease cite both the code and the underlying source articles listed below when using this \ncode in your research.\n\nA simple example script to get started is::\n\n\t>>>> # Import numpy in order to correctly read test data\n\t>>>> import numpy as np\n\n\t>>>> # Import urllib in order to download test data from Github repo\n\t>>>> import urllib\n\n\t>>>> # Append location of netrics module base directory to system path\n\t>>>> # NOTE: only required if permanent install not made \n\t>>>> # NOTE: edit path to location on netrics package on local machine\n\t>>>> import sys\n\t>>>> sys.path.append('/Users/bgraham/Dropbox/Sites/software/netrics/')\n\n\t>>>> # Load netrics module\n\t>>>> import netrics as netrics\n\t\n\t>>>> # Download Nyakatoke test dataset from GitHub\n\t>>>> download = '/Users/bgraham/Dropbox/' # Edit to location on your machine \n\t>>>> url = 'https://github.com/bryangraham/netrics/blob/master/Notebooks/Nyakatoke_Example.npz?raw=true'\n\t>>>> urllib.urlretrieve(url, download + \"Nyakatoke_Example.npz\")\n\n\t>>>> # Open dataset\n\t>>>> NyakatokeTestDataset = np.load(download + \"Nyakatoke_Example.npz\")\n\n\t>>>> # Extract adjacency matrix\n\t>>>> D = NyakatokeTestDataset['D']\n\n\t>>>> # Initialize list of dyad-specific covariates as elements\n\t>>>> # W = [W0, W1, W2,...WK-1]\n\t>>>> W = []\n\n\t>>>> # Initialize list with covariate labels\n\t>>>> cov_names = []\n\n\t>>>> # Construct list of regressor matrices and corresponding variable names\n\t>>>> for matrix in NyakatokeTestDataset.files:\n\t>>>> if matrix != 'D':\n\t>>>> W.append(NyakatokeTestDataset[matrix])\n\t>>>> cov_names.append(matrix) \n\n\t>>>> # Apply tetrad logit procedure to dataset\t\n\t>>>> [beta_TL, vcov_beta_TL, tetrad_frac_TL, success] = \\\n \t \t netrics.tetrad_logit(D, W, dtcon=None, silent=False, W_names=cov_names)\n\n\nCODE CITATION\n---------------\nGraham, Bryan S. (2016). \"netrics: a Python 2.7 package for econometric analysis of \n\tnetworks,\" (Version 0.0.1) [Computer program]. Available at \n\thttps://github.com/bryangraham/netrics (Accessed 04 September 2016) \n\t\nPAPER CITATIONS\n---------------\nGraham, Bryan S. 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