rq.bin(formula, tau = 0.5, data, weights = NULL, contrasts = NULL,
normalize = "last", control = NULL, fit = TRUE)
rqbin.fit(x, y, tau = 0.5, weights, control)rq.bin containing the following componentscoefficients is a named matrix of coefficients when tau is a vector of values.last).weights = NULL).rqbinControl).rqbin.fit calls the Fortran routine simann.f implementing the simulated annealing algorithm of Goffe et al (1994) -- original code by William Goffe, modified by Gregory Kordas. Normalization is necessary for estimation to be possible. The normalization proposed by Horowitz (1992) assumes that there is a continuous regressor independent of the (latent) error and the corresponding regression coefficient is constrained to be equal to 1. Therefore, the user must ensure that the last term in formula or the last column in the matrix x corresponds to such regressor. If the argument normalize = "all", then the normalization proposed by Manski (1975) is applied so that the norm of the vector with all the 'slopes' (i.e., excluding the intercept), is equal to 1.