Dear John, A real life example is available at https://doi.org/10.5281/zenodo.2784012. The idea is that the database returns a randomised set of points. You need to overlay these points with your sampling framework. The final sample is the set of points with the lowest ranking. The grtsdb package is a reimplementation of my GRTS package (https://github.com/ThierryO/grts). That package has a vignette describing GRTS via the Reversed Randomized Quadrant-Recursive Raster strategy ( https://doi.org/10.1007/s00267-005-0199-x).
Best regards, ir. Thierry Onkelinx Statisticus / Statistician Vlaamse Overheid / Government of Flanders INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND FOREST Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance thierry.onkel...@inbo.be Havenlaan 88 bus 73, 1000 Brussel www.inbo.be /////////////////////////////////////////////////////////////////////////////////////////// To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of. ~ Sir Ronald Aylmer Fisher The plural of anecdote is not data. ~ Roger Brinner The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data. ~ John Tukey /////////////////////////////////////////////////////////////////////////////////////////// <https://www.inbo.be> Op vr 8 okt. 2021 om 16:08 schreef John Wilson <jhwilson...@gmail.com>: > Dear Thierry, > > Thank you so much for your reply. Yes, the loss of the spatial balance > once the two-tiered approach is not accounted for was what was worrying me. > > The incorporation of region as a random effect has two issues - 1) the > overall sampling area is a lake, and "regions" don't make sense in that > context. 2) The analysis is a mark-recapture for fish (using the MARK > software); I've never seen the incorporation of random effects in the > Jolly-Seber / Cormark-Jolly-Seber models outside of Bayesian framework and > outside of individual random effects... but even if I could do that - the > regions just don't really make sense anyway (that I can see, anyway - maybe > I'm not thinking about it the right way?) > > Thank you for the grtsdb suggestion. Do you have any examples of how this > works? I couldn't find any vignettes or worked examples... > > Thank you so much, > John > > On Fri, Oct 8, 2021 at 10:39 AM Thierry Onkelinx <thierry.onkel...@inbo.be> > wrote: > >> Dear John, >> >> Your procedure will create a spatially balanced level 1 sample (10 >> "regions") and within those regions a spatially balanced level 2 sample. >> When you ignore the structure, there is no longer a spatial balance. So >> you'll need to incorporate the two level sampling structure in your >> analysis. E.g. by using region as random effect. >> >> I presume you are catching fish along rivers and assume that the rivers >> are linear features. I'd consider drawing 10 samples using GRTS to define >> the regions. Then use that location as the center point of 5 systematic >> samples along the river (-2, -1, 0, +1 and +2 km). >> >> You might want to take a look at our grtsdb package. Available at >> https://inbo.r-universe.dev/ It generates a full grid of master samples >> and stores it in the database. So you can draw multiple samples from the >> same master sample. This is useful in case of monitoring with a changing >> population. You draw a sample and keep the lowest ranking locations that >> are part of the population. If the population changes over time, then the >> new sample will keep a proportion of the original sampling location >> relative to the proportion of the population that remained stable. This >> allows for repeated measures for stable locations while taking into account >> the changes in population. >> >> Best regards, >> >> Thierry >> >> ir. Thierry Onkelinx >> Statisticus / Statistician >> >> Vlaamse Overheid / Government of Flanders >> INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE >> AND FOREST >> Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance >> thierry.onkel...@inbo.be >> Havenlaan 88 bus 73, 1000 Brussel >> www.inbo.be >> >> >> /////////////////////////////////////////////////////////////////////////////////////////// >> To call in the statistician after the experiment is done may be no more >> than asking him to perform a post-mortem examination: he may be able to say >> what the experiment died of. ~ Sir Ronald Aylmer Fisher >> The plural of anecdote is not data. ~ Roger Brinner >> The combination of some data and an aching desire for an answer does not >> ensure that a reasonable answer can be extracted from a given body of data. >> ~ John Tukey >> >> /////////////////////////////////////////////////////////////////////////////////////////// >> >> <https://www.inbo.be> >> >> >> Op do 7 okt. 2021 om 15:54 schreef John Wilson <jhwilson...@gmail.com>: >> >>> Oh, sorry - I normally use the grts() function from the spsurvey package. >>> My hacky approach was to make 10 balanced points with grts(), followed by >>> imposing a 5 km buffer around each one, and either systematic sampling >>> within the buffer circle, or running a separate GRTS for the 5 points >>> within each 5 km buffer circle. Even writing this makes me cringe though, >>> so hoping for something legitimate... I'll contact the authors if I don't >>> get any solid leads on here. >>> >>> On Thu, Oct 7, 2021 at 10:40 AM Roger Bivand <roger.biv...@nhh.no> >>> wrote: >>> >>> > On Thu, 7 Oct 2021, John Wilson wrote: >>> > >>> > > Hi everyone, >>> > > >>> > > I'm working on a sampling design using GRTS, but I'm running into a >>> > > logistics problem. The field crew can set 5 nets per day, but only >>> > within a >>> > > 5 km stretch, due to travel time constraints. With 10 sampling days, >>> > that's >>> > > a total of 50 sites. The overall sampling area is huge, so running a >>> > > regular GRTS design for 50 sites results, of course, in much larger >>> > > distances between sampling points. >>> > > >>> > > Is there a legitimate way to create a 2-level GRTS design, where in >>> step >>> > 1 >>> > > we choose 10 spatially-balanced sampling points (one "core" point per >>> > > sampling day), and then for each of these "core points", we create a >>> grid >>> > > of 5 sampling points that are constrained to all be within 5 km from >>> each >>> > > other? I can make that happen code-wise, but am not sure what the >>> > > implications on spatial balance are, or if there's a built-in way to >>> do >>> > > this. >>> > >>> > Do you have a code example? Are you using BalancedSampling, SDraw or >>> > Spbsampling or packages (probably SDraw)? Have you run any simulations >>> to >>> > try to get a first assessment on the impact of constraining your >>> sample? >>> > Might approach a package author also help? >>> > >>> > Roger >>> > >>> > >>> > > >>> > > Would appreciate any thoughts... >>> > > John >>> > > >>> > > [[alternative HTML version deleted]] >>> > > >>> > > _______________________________________________ >>> > > R-sig-Geo mailing list >>> > > R-sig-Geo@r-project.org >>> > > https://stat.ethz.ch/mailman/listinfo/r-sig-geo >>> > > >>> > >>> > -- >>> > Roger Bivand >>> > Emeritus Professor >>> > Department of Economics, Norwegian School of Economics, >>> > Postboks 3490 Ytre Sandviken, 5045 Bergen, Norway. >>> > e-mail: roger.biv...@nhh.no >>> > https://orcid.org/0000-0003-2392-6140 >>> > https://scholar.google.no/citations?user=AWeghB0AAAAJ&hl=en >>> > >>> >>> [[alternative HTML version deleted]] >>> >>> _______________________________________________ >>> R-sig-Geo mailing list >>> R-sig-Geo@r-project.org >>> https://stat.ethz.ch/mailman/listinfo/r-sig-geo >>> >> [[alternative HTML version deleted]] _______________________________________________ R-sig-Geo mailing list R-sig-Geo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
