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SecDim (version 3.2)

The Second Dimension of Spatial Association

Description

Most of the current methods explore spatial association using observations at sample locations, which are defined as the first dimension of spatial association (FDA). The proposed concept of the second dimension of spatial association (SDA), as described in Yongze Song (2022) , aims to extract in-depth information about the geographical environment from locations outside sample locations for exploring spatial association.

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Version

Install

install.packages('SecDim')

Monthly Downloads

35

Version

3.2

License

GPL-2

Maintainer

Yongze Song

Last Published

May 20th, 2023

Functions in SecDim (3.2)

gsdvar

Generating second-dimension variables for a spatial variable
rmvoutlier

Removing outliers.
sample_vars_fda

Spatial datasets of the first dimension variables of trace elements.
selectvarsda

Selecting variables for the SDA model
selectvarlm

Selecting variables using linear regression
sdapredvars

Preparing explanatory variables data for SDA-based prediction
vif

Fast calculation of the variance inflation factor (VIF)
sample_vars_sda

Spatial datasets of the second dimension variables of trace elements.
obs

Spatial datasets of trace elements.
grids

Spatial grid dataset.