The np Package - NexTag Supports Open Source Initiatives

npreg 91Usagenpreg(bws, ...)## S3 method for class 'formula':npreg(bws, data = NULL, newdata = NULL, ...)## S3 method for class 'call':npreg(bws, ...)## Default S3 method:npreg(bws,txdat = stop("training data 'txdat' missing"),tydat = stop("training data 'tydat' missing"),exdat,eydat,gradients,residuals,...)## S3 method for class 'rbandwidth':npreg(bws,txdat = stop("training data 'txdat' missing"),tydat = stop("training data 'tydat' missing"),exdat,eydat,gradients = FALSE,residuals = FALSE,...)Argumentsbwsa bandwidth specification. This can be set as a rbandwidth object returnedfrom an invocation of npregbw, or as a vector of bandwidths, with each elementi corresponding to the bandwidth for column i in txdat. If specifiedas a vector, then additional arguments will need to be supplied as necessary tospecify the bandwidth type, kernel types, and so on.... additional arguments supplied to specify the regression type, bandwidth type,kernel types, training data, and so on, detailed below.datanewdatatxdatan optional data frame, list or environment (or object coercible to a data frame byas.data.frame) containing the variables in the model. If not found in data,the variables are taken from environment(bws), typically the environmentfrom which npregbw was called.An optional data frame in which to look for evaluation data. If omitted, thetraining data are used.a p-variate data frame of explanatory data (training data) used to calculate the regressionestimators. Defaults to the training data used to compute the bandwidthobject.