mgwr.sel_bw.Sel_BW¶

Sel_BW.search(search_method='golden_section', criterion='AICc', bw_min=None, bw_max=None, interval=0.0, tol=1e-06, max_iter=200, init_multi=None, tol_multi=1e-05, rss_score=False, max_iter_multi=200, multi_bw_min=[None], multi_bw_max=[None])[source]¶

Method to select one unique bandwidth for a gwr model or a bandwidth vector for a mgwr model.

Parameters:

Parameters:	criterion : string bw selection criterion: ‘AICc’, ‘AIC’, ‘BIC’, ‘CV’ search_method : string bw search method: ‘golden’, ‘interval’ bw_min : float min value used in bandwidth search bw_max : float max value used in bandwidth search multi_bw_min : list min values used for each covariate in mgwr bandwidth search. Must be either a single value or have one value for each covariate including the intercept multi_bw_max : list max values used for each covariate in mgwr bandwidth search. Must be either a single value or have one value for each covariate including the intercept interval : float interval increment used in interval search tol : float tolerance used to determine convergence max_iter : integer max iterations if no convergence to tol init_multi : float None (default) to initialize MGWR with a bandwidth derived from GWR. Otherwise this option will choose the bandwidth to initialize MGWR with. tol_multi : convergence tolerence for the multiple bandwidth backfitting algorithm; a larger tolerance may stop the algorith faster though it may result in a less optimal model max_iter_multi : max iterations if no convergence to tol for multiple bandwidth backfittign algorithm rss_score : True to use the residual sum of sqaures to evaluate each iteration of the multiple bandwidth backfitting routine and False to use a smooth function; default is False
Returns:	bw : scalar or array optimal bandwidth value or values; returns scalar for multi=False and array for multi=True; ordering of bandwidths matches the ordering of the covariates (columns) of the designs matrix, X

criterion : string: bw selection criterion: ‘AICc’, ‘AIC’, ‘BIC’, ‘CV’
search_method : string: bw search method: ‘golden’, ‘interval’
bw_min : float: min value used in bandwidth search
bw_max : float: max value used in bandwidth search
multi_bw_min : list: min values used for each covariate in mgwr bandwidth search. Must be either a single value or have one value for each covariate including the intercept
multi_bw_max : list: max values used for each covariate in mgwr bandwidth search. Must be either a single value or have one value for each covariate including the intercept
interval : float: interval increment used in interval search
tol : float: tolerance used to determine convergence
max_iter : integer: max iterations if no convergence to tol
init_multi : float: None (default) to initialize MGWR with a bandwidth derived from GWR. Otherwise this option will choose the bandwidth to initialize MGWR with.
tol_multi : convergence tolerence for the multiple bandwidth: backfitting algorithm; a larger tolerance may stop the algorith faster though it may result in a less optimal model
max_iter_multi : max iterations if no convergence to tol for multiple: bandwidth backfittign algorithm
rss_score : True to use the residual sum of sqaures to evaluate: each iteration of the multiple bandwidth backfitting routine and False to use a smooth function; default is False

Returns:

bw : scalar or array: optimal bandwidth value or values; returns scalar for multi=False and array for multi=True; ordering of bandwidths matches the ordering of the covariates (columns) of the designs matrix, X