tds_mgwr {mgwrsar} | R Documentation |
Top-Down Scaling approach of multiscale GWR
Description
This function performs a multiscale Geographically Weighted Regression (GWR) using a top-down scaling approach, adjusting GWR coefficients with a progressively decreasing bandwidth as long as the AICc criterion improves.
Usage
tds_mgwr(formula,data,coords,Model='tds_mgwr',kernels='triangle',
fixed_vars=NULL,H2=NULL,control_tds=list(nns=30,get_AIC=FALSE),
control=list(adaptive=TRUE))
Arguments
formula |
a formula. |
data |
a dataframe. |
coords |
default NULL, a dataframe or a matrix with coordinates |
Model |
character containing the type of model: Possible values are "tds_mgwr" and "atds_mgwr", See Details for more explanation. |
kernels |
A vector containing the kernel types. Possible types: triangle ("triangle"), rectangle ("rectangle"), bisquare ("bisq"), tricube ("tcub"), gaussian ("gauss"), epanechnikov ("epane"). |
fixed_vars |
a vector with the names of spatiallay constant coefficient for mixed model. All other variables present in formula are supposed to be spatially varying. If empty or NULL (default), all variables in formula are supposed to be spatially varying. |
H2 |
A scalar or vector of time bandwidths. |
control_tds |
list of extra control arguments for tds_mgwr models |
control |
list of extra control arguments for MGWRSAR wrapper |
Details
- nns
Length of the sequence of decreasing bandwidth. Should be between 20 and 100, default 30
- get_AIC
Boolean, if the Global AICc using Yu et al 2019 should be computed. Required if the second stage 'atds_mgwr' has to be estimated. default FALSE
- init_model
Starting model, 'GWR' or 'OLS', 'default OLS'.
- model_stage1
If model='tds_mgwr', model_stage1 can be used as a starting model (either a GWR model or a preious tds_mgwr model). For model='atds_mgwr, the user can specified an tds_mgwr model already computed with get_AIC=TRUE. default NULL.
- doMC
Parallel computation, default FALSE.
- ncore
number of CPU core for parallel computation, default 1
- tol
Tolerance for stopping criteria, default 0.0001
- nrounds
Number of nrounds for 'atds_mgwr' model. Default 3.
- verbose
verbose mode, default FALSE.
- V
A vector of decreasing bandwidths given by the user, default NULL
- first_nn
The value of the highest bandwidth for the sequence of decreasing bandwidth, default NULL.
- minv
The value of the smallest bandwidth for the sequence of decreasing bandwidth, default number of covariates + 2 .
- H
A vector of bandwidth, default NULL
- Z
A matrix of variables for genralized kernel product, default NULL.
- W
A row-standardized spatial weight matrix for Spatial Aurocorrelation, default NULL.
- type
Verbose mode, default FALSE.
- adaptive
A vector of boolean to choose adaptive version for each kernel.
- kernel_w
The type of kernel for computing W, default NULL.
- h_w
The bandwidth value for computing W, default 0.
- Method
Estimation method for computing the models with Spatial Dependence. '2SLS' or 'B2SLS', default '2SLS'.
- TP
Avector of target points, default NULL.
- doMC
Parallel computation, default FALSE. If TRUE and control_tds$doMC is also TRUE, then control$doMC is set to FALSE.
- ncore
Number of CPU core for parallel computation, default 1
- isgcv
If TRUE, compute a LOOCV criteria, default FALSE.
- isfgcv
If TRUE, simplify the computation of CV criteria (remove or not i when using local instruments for model with lambda spatially varying), default TRUE.
- maxknn
When n >NmaxDist, only the maxknn first neighbours are used for distance compution, default 500.
- NmaxDist
When n >NmaxDist only the maxknn first neighbours are used for distance compution, default 5000
- verbose
Verbose mode, default FALSE.
See Also
gwr_multiscale, MGWRSAR, bandwidths_mgwrsar, summary_mgwrsar.