MRSea and MRSeaPower
MRSea
Marine renewables strategic environmental assessment
Software for fitting one and two dimensional spatially adaptive smoothing splines. This software was developed for the marine renewables framework but is suitable for most smoothing applications. Information about the package and tutorials can be found on the website.
Email comments to: [email protected]
For the latest package release, please download from here or use the following code in R:
> devtools::install_github(repo = "lindesaysh/MRSea", ref="stable")
For the development version of MRSea, please use the following code in R to install:
> devtools::install_github(repo = "lindesaysh/MRSea", ref = "master")
References/Documentation
- Package:
- Scott-Hayward, L.A.S., Walker, C.G. and M.L. Mackenzie (2021). Vignette for the MRSea Package v1.3: Statistical Modelling of bird and cetacean distributions in offshore renewables development areas. Centre for Research into Ecological and Environmental Modelling, University of St Andrews.
- Mackenzie, M.L, Scott-Hayward, L.A.S., Oedekoven, C.S., Skov, H., Humphreys, E., and Rexstad E. (2013). Statistical Modelling of Seabird and Cetacean data: Guidance Document. University of St. Andrews contract for Marine Scotland; SB9 (CR/2012/05).
- CReSS smoothing:
- Scott-Hayward, L., Mackenzie, M. L., Donovan, C. R., Walker, C. G., and Ashe, E. (2013). Complex Region Spatial Smoother (CReSS). Journal of Computational and Graphical Statistics.
- Scott-Hayward, L., Mackenzie, M. L., Ashe, E. and R. Williams (2015). Modelling Killer whale feeding behaviour using a spatially adaptive complex region spatial smoother (CReSS) and generalised estimating equations (GEEs). Journal of Agricultural, Biological and Environmental Statistics,, 20, 305-322.
- SALSA1D:
- Walker, C., Mackenzie, M., Donovan, C., and O’Sullivan, M. (2011). SALSA – a Spatially Adaptive Local Smoothing Algorithm. Journal of Statistical Computation and Simulation 81, 179-191.
- SALSA 2D:
- Scott-Hayward, L.A.S., M.L. Mackenzie, C.G. Walker, G. Shatumbu, JW. Kilian, P. du Preez, M Hauptfleisch and C. Cloete (2025). Assessing the distribution pattern of elephant (Loxodonta africana) carcasses in Etosha National Park and its implications for management. Namibian Journal of Environment, 10, 1-12. ISSN: 2026-8327 (online)
MRSeaPower
Power analysis methods for assessing the Power to Detect Change.
Software for implementing spatially explicit power analyses for gamMRSea models. The original development was undertaken by CREEM on behalf of the Scottish Government. Information about the package and tutorials can be found on the website.
R package
For the latest package release, please download from here.
For the development version of MRSeaPower, please use the following code in R to install:
devtools::install_github(repo = "lindesaysh/MRSeaPower", ref = "development")
References/Documentation
Mackenzie, M.L., Scott-Hayward, L.A.S., Paxton, C.G. and M.L. Burt (2017). Quantifying the Power to Detect Change: methodological development and implementation using the R package MRSeaPower.
Scott-Hayward, L.A.S. and M.L. Mackenzie (2017). MRSeaPower: Power analysis method for gamMRSea models. R package version 1.0.