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        "author": "Feras El Zarwi and Akshay Vij",
        "author_email": "feraselzarwi@gmail.com, vij.akshay@gmail.com",
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            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: BSD License",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Topic :: Scientific/Engineering"
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        "description": "What Lccm is\r\n===============\r\nLccm is a Python package for estimating latent class choice models \r\nusing the Expectation Maximization (EM) algorithm to maximize the likelihood function.\r\n\r\nMain Features\r\n=============\r\n\r\nLatent Class Choice Models\r\n\r\n* Supports datasets where the choice set differs across observations.\r\n* Allows the analyst to capture correlation across multiple observations for the same respondent (panel data in Revealed Preference contexts and multiple choice tasks in Stated Preference contexts).\r\n* Supports model specifications where the coefficient for a given variable may be generic (same coefficient across all alternatives) or alternative specific (coefficients varying across all alternatives or subsets of alternatives) in each latent class.\r\n* Accounts for sampling weights in case the data you are working with is choice-based i.e. Weighted Exogenous Sample Maximum Likelihood (WESML) from (Ben-Akiva and Lerman, 1983) to yield consistent estimates.\r\n* Constrains the choice set across latent classes whereby each latent class can have its own subset of alternatives in the respective choice set.\r\n* Constrains the availability of latent classes to all individuals in the sample whereby it might be the case that a certain latent class or set of latent classes are unavailable to certain decision-makers.\r\n\r\nWhere to get it\r\n===============\r\nAvailable from PyPi::\r\n    pip install lccm\r\n\r\n    https://pypi.python.org/pypi/lccm/0.1.20\r\n\r\n\r\nFor More Information\r\n====================\r\nFor more information about the lccm code, see the following dissertation:\r\n    El Zarwi, Feras. \"Modeling and Forecasting the Impact of Major Technological and Infrastructural Changes on Travel Demand\", PhD Dissertation, 2017, University of California at Berkeley.\r\n\r\nAttribution\r\n===========\r\nIf Lccm is useful in your research or work, please cite this package by citing the dissertation above and the package itself.\r\n\r\nLicense\r\n=======\r\nModified BSD (3-clause)\r\n\r\nChangelog\r\n=========\r\n\r\n0.1.20 (April 21st, 2017)\r\n-------------------------\r\n- Initial package release for estimating latent class choice models using the Expectation Maximization Algorithm.",
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