midrqControl: Control parameters for midrq estimation

In marco-geraci/Qtools: Utilities for Quantiles

Control parameters for midrq estimation

Description

A list of parameters for controlling the fitting process.

Usage

midrqControl(method = "Nelder-Mead", ecdf_est = "npc", npc_args = list())

Arguments

method	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.
ecdf_est	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.
npc_args	named list of arguments for npcdistbw when ecdf_est = npc.

Value

a list of control parameters.

Author(s)

Marco Geraci

References

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.

See Also

midrq

marco-geraci/Qtools documentation built on Sept. 4, 2023, 7:07 p.m.