autofitVariogramST: Automatically fit a spatiotemporal variogram from sftime or...
In sigmafelix/autoSTK: Automatic spatio-temporal kriging

View source: R/autofitVariogramST.r

autofitVariogramST

R Documentation

Automatically fit a spatiotemporal variogram from sftime or ST*DF

Usage

autofitVariogramST(
                   stf,
                   formula,
                   typestv ='sumMetric',
                   candidate_model = c('Ste','Exc','Exp','Wav'),
                   guess_nugget = NULL,
                   guess_psill = NULL,
                   tlags = 0:6,
                   cutoff = 2e4,
                   width = 5e2,
                   aniso_method = 'vgm',
                   type_joint = 'Exp',
                   prodsum_k = NULL,
                   surface = FALSE,
                   cores = 1
                       )

Arguments

`stf`	An object of the sftime, STI or STF containing the data from which the spatiotemporal variogram to be estimated.
`formula`	formula that defines the dependent variable as a linear model of independent variables; suppose the dependent variable has name 'z', for ordinary and simple kriging use the formula 'z~1'; for simple kriging also define 'beta' (see below); for universal kriging, suppose 'z' is linearly dependent on 'x' and 'y', use the formula 'z~x+y'.
`typestv`	Model for the spatiotemporal variogram
`candidate_model`	List of models that will be tested during automatic variogram fitting. Default values are "Sph", "Exp", "Gau", and "Ste"
`guess_nugget`	A user-defined value for the nugget of the spatiotemporal variogram.
`guess_psill`	A user-defined value for the partial sill of the spatiotemporal variogram
`tlags`	The range of time lags for fitting STVariogram
`cutoff`	The maximum range of spatial lags for fitting STVariogram
`width`	The interval for fitting spatial part of the STVariogram
`aniso_method`	The method to estimate the spatiotemporal anisotropy (one of `linear`, `range`, `vgm`, or `metric`)
`type_joint`	The type of theoretical model of the joint spatiotemporal variogram. Only applied when `joint` type of spatiotemporal variogram is chosen.
`prodsum_k`	k value for `stModel` in vgmST is `productSum`. See vgmST for more.

#

`surface`	`logical`. Set `TRUE` if you want to get the wireframe plot of the fitted spatiotemporal variogram
`cores`	The number of cores to be used for estimating variogramST. See variogramST for detail.

Value

`jointSTV`	The fitted theoretical spatiotemporal variogram
`empSTV`	The empirical spatiotemporal variogram estimated from the input data
`SpV`	The spatial component of `jointSTV`
`TV`	The temporal component of `jointSTV`
`STVsurface`	`data.frame`. The variogram surface of `jointSTV`