TSCS {TSCS} | R Documentation |
A Package for TSCS Spatial Interpolation Method
Description
This package provides functions to implement TSCS spatial interpolation and relevant data visualization. For TSCS method, the current version is only able to make use of spatio-temporal data whose spatial domain is a 2D or 3D rectangular grid system.
Details
TSCS (abbr. of Time Series Cointegrated System) method is a spatial interpolation method based on analysis of historical spatio-temporal data. It can be regarded as a desirable alternative to spatio-temporal interpolation in some cases where we merely intend to interpolate a series of cross-section data at each observed time point for a given spatial domain.
The basic assumption of TSCS method is that, for any spatial location within the spatial domain of spatio-temporal data, its time series and the time series of its adjacent spatial locations are cointegrated (long-term equilibrium relationships).
As to TSCS method, package of the current version is only able to make use of spatio-temporal data whose spatial domain is a 2D or 3D rectangular grid system.
Package Functions
-
tscsRegression, tscsRegression3D
: obtains regression coefficient matrix, the first step of TSCS for 2D and 3D rectangular grid system respectively. -
tscsEstimate, tscsEstimate3D
: estimates the missing observations within a cross-section data (pure spatial data) of a particular time point you have selected, the second step of TSCS for 2D and 3D rectangular grid system respectively. -
plot_dif, plot3D_dif
: differentiates boundary and interior spatial locations in a spatial domain. -
plot_NA, plot3D_NA
: shows spatial locations with or without missing observation in a spatial domain. -
plot_map, plot3D_map
: draws the spatial map for a cross-section data. -
plot_compare
: visualizes the comparison between estimates and true values (if you have). -
appraisal_index
: computes the two appraisal indexes used for evaluating the result of interpolation/prediction - RMSE and standard deviation of error. (if you have the true values)
Author(s)
Tianjian Yang <yangtj5@mail2.sysu.edu.cn>