{ "_id": "6ac24110d743750d376d76e5", "Package": "logitr", "Title": "Logit Models w/Preference & WTP Space Utility Parameterizations", "Version": "1.2.0", "Authors@R": "c(\nperson(given = \"John\",\nfamily = \"Helveston\",\nrole = c(\"aut\", \"cre\", \"cph\"),\nemail = \"john.helveston@gmail.com\",\ncomment = c(ORCID = \"0000-0002-2657-9191\")),\nperson(given = \"Connor\",\nfamily = \"Forsythe\",\nrole = \"ctb\",\nemail = \"cforsyth@andrew.cmu.edu\"))", "Description": "Fast estimation of multinomial logit (MNL) and mixed logit\n(MXL) models. Models can be estimated using preference space or\nwillingness-to-pay (WTP) space utility parameterizations.\nWeighted models can also be estimated. An option is available\nto run a parallelized multistart optimization loop with random\nstarting points in each iteration, which is useful for\nnon-convex problems like MXL models or models with WTP space\nutility parameterizations. The main optimization loop uses the\n'nloptr' package to minimize the negative log-likelihood\nfunction. Additional functions are available for computing and\ncomparing WTP from both preference space and WTP space models\nand for predicting expected choices and choice probabilities\nfor sets of alternatives based on an estimated model. Mixed\nlogit models can include uncorrelated or correlated\nheterogeneity covariances and are estimated using maximum\nsimulated likelihood based on the algorithms in Train (2009)\n. 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