grid

spatial grid data of explanatory variables.

dataset

trace

elements

Understanding spatial association is essential for spatial
statistical inference, including factor exploration and spatial prediction.
Geographically optimal similarity (GOS) model is an effective method
for spatial prediction, as described in Yongze Song (2022)
<doi:10.1007/s11004-022-10036-8>. GOS was developed based on
the geographical similarity principle, as described in Axing Zhu (2018)
<doi:10.1080/19475683.2018.1534890>. GOS has advantages in
more accurate spatial prediction using fewer samples and
critically reduced prediction uncertainty.

Wenbo Lv

geosimilarity

Geographically Optimal Similarity

Yongze Song

grid function

<code>grid</code>: A tibble of grided trace element explanatory variables
with 13132 rows and 12 variables, where the first column is ID.

Format

Yongze Song <a href="/link/yongze.song%40outlook.com?package=geosimilarity&version=3.8" data-mini-rdoc="geosimilarity::yongze.song@outlook.com">yongze.song@outlook.com</a>

Author

spatial grid data of explanatory variables. — grid

Yongze Song <a href='mailto:yongze.song@outlook.com'>yongze.song@outlook.com</a>

grid: spatial grid data of explanatory variables.

Description

Usage

Arguments

Format

Author