quantRegSpacing.Rd
Computes coefficients for the quantile regression spacing method.
quantRegSpacing( dep_col, data, var_names, alpha, jstar, algorithm = "rq.fit.sfn_start_val", small = 0.001, trunc = FALSE, start_list = NA, weight_vec = NULL, outputQuantiles = FALSE, calculateAvgME = FALSE, lambda = NULL, ... )
dep_col | Column of response variable. |
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data | Regression specification matrix. |
var_names | RHS regression variable names. |
alpha | Quantiles to be estimated. |
jstar | First quantile to be estimated (usually the center one) |
algorithm | The name of a function which will estimate a quantile regression. Defaults to rq.fit.sfn_start_val. Must be a string, as it is passed to `do.call` |
small | Minimum size of residuals for computational accuracy. |
trunc | Boolean value; if true, replace those dependent values less than small with small itself; else, only use rows with residuals greater than small |
start_list | Starting values for regression optimization. |
weight_vec | vector of optional weights |
outputQuantiles | TRUE or FALSE, whether to output quantiles |
calculateAvgME | TRUE or FALSE, whether to output average marginal effects |
lambda | optional penalty parameter, ignored except for penalized regression algorithms |
... | other parameters passed to the algorithm |
Returns a list of coefficients. num_betas is an x by p matrix of estimated parameters for each supplied quantiles. pseudo_r is a 1 by p matrix of psuedo R^2 values for each quantile estimate. warnings is a 1 by p matrix of warnings produced by each quantile regression call. iter: is a 1 by p matrix of iterations ran by each quantile regression call.