likelihoodTools

Tools for Managing Maximum Likelihood Estimation Results

The likelihoodTools package provides tools for managing and exploring parameter estimation results derived from Maximum Likelihood Estimation (MLE) using the likelihood package. This package simplifies analysis workflows by offering functions that support the organization, visualization, and summary of MLE outcomes, aiding in deeper statistical insights.

The package is designed to simplify the exploration and interpretation of MLE results, providing a comprehensive set of tools for managing parameter estimation outcomes.

Installation

You can install the development version of likelihoodTools from GitHub with:

# install.packages("pak")
pak::pak("ajpelu/likelihoodTools")

Usage

See the Get Started vignette for a comprehensive introduction to the package.

Key Features

• Tools for organizing MLE outputs.
• Functions to explore, visualize, and interpret parameter estimation results.
• Integrations with dplyr and ggplot2 for efficient data manipulation and visualization.

A litle of history

The likelihood package was developed initially by Charles Canham and Lora Murphy from the Cary Institute of Ecosystem Studies (Milbrook, NY, US). The package was designed to facilitate the use of maximum likelihood estimation in R, using simulated annealing as the optimization routine. The implementation of simulated annealing was adapted from Goffe et al. (1994), and allows bounded searches.

The likelihood package has been used in multiple scientific studies to explore various aspects of tree forest ecology worldwide (e.g. Canham and Uriarte 2006, Canham et al. 2006, Gómez-Aparicio et al. 2009, 2011, Gea-Izquierdo et al. 2013, Fernández-de-Uña et al. 2015). Despite its broad use, it has lacked user-friendly tools for managing and exploring parameter estimation results. This gap inspired the development of the likelihoodTools package

Citation

If using this package, please cite it:

citation("likelihoodTools")
To cite package 'likelihoodTools' in publications use:

  Pérez-Luque AJ (2024). _likelihoodTools: Tools for managing results
  from Maximum Likelihood Estimation_. R package version 0.1.0,
  <https://ajpelu.github.io/likelihoodTools/>.

A BibTeX entry for LaTeX users is

  @Manual{,
    title = {likelihoodTools: Tools for managing results from Maximum Likelihood Estimation},
    author = {Antonio Jesús Pérez-Luque},
    year = {2024},
    url = {https://ajpelu.github.io/likelihoodTools/},
    note = {R package version 0.1.0},
  }

Funding

Antonio J. Pérez-Luque received funding from the Spanish Ministry of Science and Innovation through the Juan de la Cierva postdoctoral fellowship program. Grant JDC2022-050056-I funded by MCIN/AEI/ 10.13039/501100011033 and by “European Union NextGenerationEU/PRTR

References

Canham, C. D., M. J. Papaik, M. Uriarte, W. H. McWilliams, J. C. Jenkins, and M. J. Twery. 2006. Neighborhood analyses of canopy tree competition along environmental gradients in new england forests. Ecological Applications 16:540–554.

Canham, C. D., and M. Uriarte. 2006. Analysis of neighborhood dynamics of forest ecosystems using likelihood methods and modeling. Ecological Applications 16:62–73.

Fernández-de-Uña, L., I. Cañellas, and G. Gea-Izquierdo. 2015. Stand competition determines how different tree species will cope with a warming climate. PLOS ONE 10:e0122255.

Gea-Izquierdo, G., L. Fernández-de-Uña, and I. Cañellas. 2013. Growth projections reveal local vulnerability of Mediterranean oaks with rising temperatures. Forest Ecology and Management 305:282–293.

Goffe, W. L., G. D. Ferrier, and J. Rogers. 1994. Global optimization of statistical functions with simulated annealing. Journal of Econometrics 60:65–99.

Gómez-Aparicio, L., R. García-Valdés, P. Ruíz-Benito, and M. A. Zavala. 2011. Disentangling the relative importance of climate, size and competition on tree growth in iberian forests: Implications for forest management under global change: Neighborhood models and tree growth drivers. Global Change Biology 17:2400–2414.

Gómez-Aparicio, L., M. A. Zavala, F. J. Bonet, and R. Zamora. 2009. Are pine plantations valid tools for restoring Mediterranean forests? An assessment along abiotic and biotic gradients. Ecological Applications 19:2124–2141.