abr_fit.hgam: Fits an HGAM model

In regime-shifts/abrupt: Methods for detecting abrupt change in temporal, spatial, and spatiotemporal data series

Fits an HGAM model

Description

Fits an HGAM model

Usage

abr_fit.hgam(
  data,
  type = "t",
  bs_t = "tp",
  bs_s = "gp",
  bs_g = "re",
  k_t = 20,
  k_s = 20,
  k_g = NA,
  func = "gam",
  family = "gaussian",
  calc_breaks = FALSE,
  break_args = list(),
  ...
)

Arguments

data	Data frame used for fitting. Should be constructed by the abr_data function
type	The type of regime detection model. One of "t", "st","s", "gt", "gst","gs". "t" indicates a temporal smoother, "s" indicates a spatial smoother, and "g" indicates a grouped (HGAM) smoother
family	The family mgcv or brms will use to fit the model.
bs_t/bs_s/bs_g	basis types to be used for the temporal, spatial, and group-level smoothers
k_t/k_s/k_g	number of basis functions to use for temporal, spatial, and group-level smoothers

Value

A fitted object of class 'abrupt_model' and 'HGAM'.

regime-shifts/abrupt documentation built on Aug. 26, 2022, 3:15 p.m.