lagr: Fit a model via local, adaptive grouped regularization
In wrbrooks/lagr: Local adaptive grouped regularization

lagr fits a LAGR model This method fits a local model at each location indicated by fit.loc.

lagr(formula, data, family = gaussian(), weights = NULL, coords,
  fit.loc = NULL, tuning = FALSE, predict = FALSE, simulation = FALSE,
  oracle = NULL, kernel = NULL, bw = NULL, varselect.method = c("AIC",
  "BIC", "AICc", "wAIC", "wAICc"), verbose = FALSE, longlat = FALSE,
  tol.loc = NULL, bw.type = c("dist", "knn", "nen"), D = NULL,
  lambda.min.ratio = 0.001, n.lambda = 50, lagr.convergence.tol = 0.001,
  lagr.max.iter = 20, jacknife = FALSE, bootstrap.index = NULL,
  na.action = na.fail, contrasts = NULL)

`formula`	symbolic representation of the model
`data`	data frame containing observations of all the terms represented in the formula
`family`	exponential family distribution of the response
`weights`	vector of prior observation weights (due to, e.g., overdispersion). Not related to the kernel weights.
`coords`	matrix of locations, with each row giving the location at which the corresponding row of data was observed
`fit.loc`	matrix of locations where the local models should be fitted
`tuning`	logical indicating whether this model will be used to tune the bandwidth, in which case only the tuning criteria are returned
`kernel`	kernel function for generating the local observation weights
`bw`	bandwidth parameter
`varselect.method`	criterion to minimize in the regularization step of fitting local models - options are `AIC`, `AICc`, `BIC`, `GCV`
`verbose`	print detailed information about our progress?
`longlat`	`TRUE` indicates that the coordinates are specified in longitude/latitude, `FALSE` indicates Cartesian coordinates. Default is `FALSE`.
`tol.loc`	tolerance for the tuning of an adaptive bandwidth (e.g. `knn` or `nen`)
`bw.type`	type of bandwidth - options are `dist` for distance (the default), `knn` for nearest neighbors (bandwidth a proportion of `n`), and `nen` for nearest effective neighbors (bandwidth a proportion of the sum of squared residuals from a global model)
`D`	pre-specified matrix of distances between locations