A list of parameters for controlling the fitting process.
midrqControl(method = "Nelder-Mead", ecdf_est = "npc", npc_args = list())a list of control parameters.
character vector that specifies the optimization algorithm in optim to fit a conditional mid-quantile model when type = 1 or type = 2. Only "Nelder-Mead" has been tested.
estimator of the (standard) conditional cumulative distribution. The options are: npc (default) for kernel estimator (Li and Racine, 2008); logit, probit, cloglog for binomial regression; ao for Aranda-Ordaz binomial regression.
named list of arguments for npcdistbw when ecdf_est = npc.
Marco Geraci
Geraci, M. and A. Farcomeni. Mid-quantile regression for discrete responses. arXiv:1907.01945 [stat.ME]. URL: https://arxiv.org/abs/1907.01945.
Li, Q. and J. S. Racine (2008). Nonparametric estimation of conditional cdf and quantile functions with mixed categorical and continuous data. Journal of Business and Economic Statistics 26(4), 423-434.
midrq