Monte Carlo estimation of the mixed logit model using low-discrepancy sequences
Monte Carlo estimation evaluates a function at different points to compute an approximated average. Traditionally this is done at random points. Quasi-random sequences are strategically constructed deterministic points that aim to be more efficient than random points. The golden ratio has unique properties to construct low-discrepancy sequences that are compared to traditional quasi-random methods. The methods are compared by estimating the mixed multinomial logit model for panel data.
|Thesis Advisor||Castelein, A.|
Jonge van Ellemeet, T.C.W. de. (2019, July 15). Monte Carlo estimation of the mixed logit model using low-discrepancy sequences. Econometrie. Retrieved from http://hdl.handle.net/2105/50096