lagr.fit.inner: Fit a local model via the local adaptive group lasso

In wrbrooks/lagr: Local adaptive grouped regularization

Description

This function augments the covariates with local interactions, drops observations with zero weight, runs the adaptive grouped lasso, computes the residuals, and returns the necessary values for tuning or reporting.

Usage

lagr.fit.inner(x, y, group.id, coords, loc, family, varselect.method, oracle,
  tuning, predict, simulation, n.lambda, lambda.min.ratio, lagr.convergence.tol,
  lagr.max.iter, verbose, kernel.weights = NULL, prior.weights = NULL,
  longlat = FALSE)

Arguments

x	matrix of observed covariates
y	vector of observed responses
loc	location at which to fit a model
family	exponential family distribution of the response
varselect.method	criterion to minimize in the regularization step of fitting local models - options are AIC, AICc, BIC, GCV
tuning	logical indicating whether this model will be used to tune the bandwidth, in which case only the tuning criteria are returned
kernel.weights	vector of observation weights from the kernel
prior.weights	vector of prior observation weights provided by the user
longlat	TRUE indicates that the coordinates are specified in longitude/latitude, FALSE indicates Cartesian coordinates. Default is FALSE.

Value

list of coefficients, nonzero coefficient identities, and tuning data

wrbrooks/lagr documentation built on May 4, 2019, 11:59 a.m.