In lcgodoy/smile: Spatial Misalignment: Interpolation, Linkage, and Estimation

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smile

Spatial Misalignment: Interpolation, Linkage, and Estimation

The smile package for R simplifies the analysis of spatial data. It offers tools to:

• Estimate and predicte: Using a model-based approach, smile treats areal data as averages derived from a continuous Gaussian random field. It is possible to model point-referenced and areal data jointly.

• Interpolate: For straightforward interpolation, smile employs a non-parametric method known as simple areal interpolation.

• Quantify uncertainty: When dealing with simple areal interpolation and knowing the variance of your observations, smile helps you quantify the uncertainty associated with the interpolation.

Essentially, smile provides a user-friendly way to explore, model, and interpolate spatial data with R, offering both model-based and non-parametric approaches.

The package accompanies a web page (powered by pkgdown) and 5 vignettes.

Vignettes

1. Converting sf to spm objects;
2. Fitting models and making predictions;
3. Areal Interpolation;
4. Method;
5. Spatial covariance functions;

Installation

To install the CRAN version of the package, use

install.packages("smile")

The installation of the development version from GitHub can be done via

remotes::install_github("lcgodoy/smile")
## or devtools::install_github("lcgodoy/smile")

lcgodoy/smile documentation built on Nov. 20, 2024, 12:17 a.m.