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BMEmapping

Spatial Interpolation using Bayesian Maximum Entropy (BME)

https://github.com/kinsprideduah/bmemapping

Science Score: 26.0%

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Keywords

bayesian-maximum-entropy spatial-interpolatio
Last synced: 10 months ago · JSON representation

Repository

Spatial Interpolation using Bayesian Maximum Entropy (BME)

Basic Info
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 5
  • Releases: 1
Topics
bayesian-maximum-entropy spatial-interpolatio
Created over 1 year ago · Last pushed 10 months ago
Metadata Files
Readme Changelog License

README.Rmd 

---
output: github_document
---


  
```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

### Spatial Interpolation for data comprising hard and soft-interval forms

The **Bayesian Maximum Entropy (BME)** framework provides a flexible and principled approach to space-time data analysis by combining Bayesian inference with the maximum entropy principle. It supports optimal estimation using both precise (hard) and uncertain (soft) data, such as intervals or probability distributions—making it ideal for complex, real-world datasets. The **BMEmapping** R package implements core BME methods for spatial interpolation, enabling the integration of heterogeneous data, variogram-based modeling, and uncertainty quantification. 

## Installation

You can install the development version of **BMEmapping** from
[GitHub](https://github.com/) with:

``` r
# install.packages("devtools")
devtools::install_github("KinsprideDuah/BMEmapping")
```

## Functions

`bme_map` - creates a `BMEmapping` object that contains all the data information necessary for BME interpolation.

`prob_zk` - computes and optionally plots the posterior density estimate at a single unobserved location.

`bme_predict` - predicts the posterior mean or mode and the associated variance at an unobserved location.

`bme_cv` - performs a cross-validation on the hard data to assess model performance.


## Getting help

If you encounter a clear bug, please file an issue with a minimal
reproducible example on
[GitHub](https://github.com/KinsprideDuah/BMEmapping/issues).

## Author

Kinspride Duah

## License

MIT + file LICENSE

Owner

  • Name: Kinspride Duah
  • Login: KinsprideDuah
  • Kind: user

GitHub Events

Total
  • Create event: 9
  • Release event: 1
  • Issues event: 5
  • Public event: 1
  • Push event: 36
Last Year
  • Create event: 9
  • Release event: 1
  • Issues event: 5
  • Public event: 1
  • Push event: 36

Packages

  • Total packages: 1
  • Total downloads:
    • cran 322 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 4
  • Total maintainers: 1
cran.r-project.org: BMEmapping

Spatial Interpolation using Bayesian Maximum Entropy (BME)

  • Versions: 4
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 322 Last month
Rankings
Dependent packages count: 26.5%
Forks count: 29.0%
Dependent repos count: 32.7%
Stargazers count: 37.3%
Average: 42.4%
Downloads: 86.7%
Maintainers (1)
kinspride2020@gmail.com
Last synced: 10 months ago

Dependencies

.github/workflows/R-CMD-check.yaml actions
  • actions/checkout v4 composite
  • r-lib/actions/check-r-package v2 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite
DESCRIPTION cran
  • R >= 3.5 depends
  • mvtnorm * imports
  • knitr * suggests
  • rmarkdown * suggests
  • testthat >= 3.0.0 suggests