Fast estimation of multinomial (MNL) and mixed logit (MXL) models in R with "Preference" space or "Willingness-to-pay" (WTP) space utility parameterizations in R
Following the conversation in #53, it'd be great to be able to call {xlogit} (python) from {logitr} to be able to access the amazing estimation speed and capabilities that {xlogit} has to offer. In particular, {logitr} (and basically all other packages) struggle to estimate mixed logit models with a large number of draws (~>1,000), but {xlogit} can easily handle orders of magnitude more draws in extremely fast time periods due to it's use of CPUs. I imagine this could be implemented via the {reticulate} package and with an additional argument like xlogit = TRUE to trigger the use of {xlogit} to estimate the model.
Following the conversation in #53, it'd be great to be able to call {xlogit} (python) from {logitr} to be able to access the amazing estimation speed and capabilities that {xlogit} has to offer. In particular, {logitr} (and basically all other packages) struggle to estimate mixed logit models with a large number of draws (~>1,000), but {xlogit} can easily handle orders of magnitude more draws in extremely fast time periods due to it's use of CPUs. I imagine this could be implemented via the {reticulate} package and with an additional argument like
xlogit = TRUEto trigger the use of {xlogit} to estimate the model.