rq.fit.sfn_start_val.Rd
Sparse Regression Quantile Fitting with Weights
rq.fit.sfn_start_val( X, y, tau = 0.5, rhs = (1 - tau) * c(t(a) %*% rep(1, length(y))), control, sv, weights = NULL, lambda, ... )
X | structure of the design matrix X stored in csr format |
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y | outcome vector |
tau | desired quantile |
rhs | the right-hand-side of the dual problem; regular users shouldn't need to specify this, but in special cases can be quite usefully altered to meet special needs. See e.g. Section 6.8 of Koenker (2005). |
control | control parameters for fitting routines: see |
sv | starting value for optimization, useful when bootstrapping |
weights | Optional vector of weights for regression |
lambda | ignored |
... | other parameters, ignored |
A wrapper around the rq.fit.sfn function from the quantreg package, extended to allow for a user-supplied starting value and weights