Hi John, I haven't read that particular paper but in answer to your question...
> So if i do this for all the families it will be the same as doing the > simulation experiment > outline in the method above? Yes :) Michael On 15 October 2010 23:18, John Haart <anothe...@me.com> wrote: > Hi Michael, > > Thanks for this - the reason i am following this approach is that it appeared > in a paper i was reading, and i thought it was a interesting angle to take > > The paper is > > Vamosi & Wilson, 2008. Nonrandom extinction leads to elevated loss of > angiosperm evolutionary history. Ecology Letters, (2008) 11: 1047–1053. > > and the specific method i am following states :- > >> We calculated the number of species expected to be at risk in each family >> under a random binomial distribution in 10 000 randomizations [generated >> using R version 2.6.0 (R Development Team 2007)] assuming every species has >> a 7.48% chance of being at risk. > > I guess the reason i am doing the simulation is because i am not hugely > statistically minded and the paper was asking the same question i am > interested in answering :). > > So following your approach - > >> if family F has Fn species, your random expectation is that p * Fn of >> them will be at risk (p = 0.0748). The variance on that expectation >> will be p * (1-p) * Fn. > > > Family f = Bromeliaceae , with Fn = 80, p=0.0748 > random expectation = p*Fn = (0.0748*80) = 5.984 > variance = p * (1-p) * Fn = (0.0748*0.9252) *80 = 5.5363968 > > So the random expectation is that the Bromeliaceae will have 6 species at > risk, if risk is assigned randomly? > > So if i do this for all the families it will be the same as doing the > simulation experiment outline in the method above? > > Thanks > > John > > > > > On 15 Oct 2010, at 12:49, Michael Bedward wrote: > > Hi John, > > The word "species" attracted my attention :) > > Like Dennis, I'm not sure I understand your idea properly. In > particular, I don't see what you need the simulation for. > > If family F has Fn species, your random expectation is that p * Fn of > them will be at risk (p = 0.0748). The variance on that expectation > will be p * (1-p) * Fn. > > If you do your simulation that's the result you'll get. Perhaps to > initial identify families with disproportionate observed extinction > rates all you need is the dbinom function ? > > Michael > > > On 15 October 2010 22:29, John Haart <anothe...@me.com> wrote: >> Hi Denis and list >> >> Thanks for this , and sorry for not providing enough information >> >> First let me put the study into a bit more context : - >> >> I know the number of species at risk in each family, what i am asking is >> "Is risk random according to family or do certain families have a >> disproportionate number of at risk species?" >> >> My idea was to randomly allocate risk to the families based on the criteria >> below (binomial(nspecies, 0.0748)) and then compare this to the "true data" >> and see if there was a significant difference. >> >> So in answer to your questions, (assuming my method is correct !) >> >>> Is this over all families, or within a particular family? If the former, why >>> does a distinction of family matter? >> >> Within a particular family - this is because i am looking to see if risk in >> the "observed" data set is random in respect to family so this will provide >> the baseline to compare against. >> >>> I guess you've stated the p, but what's the n? The number of species in each >>> family? >> >> This varies largely, for instance i have some families that are monotypic >> (with 1 species) and then i have other families with 100+ species >> >> >>> Assuming you have multiple families, do you want separate simulations per >>> family, or do you want to do some sort of weighting (perhaps proportional to >>> size) over all families? >> >> I am assuming i want some sort of weighting. This is because i am wanting to >> calculate the number of species expected to be at risk in EACH family under >> the random binomial distribution ( assuming every species has a 7.48% chance >> of being at risk. >> >> Thanks >> >> John >> >> >> >> >> On 15 Oct 2010, at 11:19, Dennis Murphy wrote: >> >> Hi: >> >> I don't believe you've provided quite enough information just yet... >> >> On Fri, Oct 15, 2010 at 2:22 AM, John Haart <anothe...@me.com> wrote: >> >>> Dear List, >>> >>> I am doing some simulation in R and need basic help! >>> >>> I have a list of animal families for which i know the number of species in >>> each family. >>> >>> I am working under the assumption that a species has a 7.48% chance of >>> being at risk. >>> >> >> Is this over all families, or within a particular family? If the former, why >> does a distinction of family matter? >> >>> >>> I want to simulate the number of species expected to be at risk under a >>> random binomial distribution with 10,000 randomizations. >>> >> >> I guess you've stated the p, but what's the n? The number of species in each >> family? If you're simulating on a family by family basis, then it would seem >> that a binomial(nspecies, 0.0748) distribution would be the reference. >> Assuming you have multiple families, do you want separate simulations per >> family, or do you want to do some sort of weighting (perhaps proportional to >> size) over all families? The latter is doable, but it would require a >> two-stage simulation: one to randomly select a family and then to randomly >> select a species. >> >> Dennis >> >> >>> >>> I am relatively knew to this field and would greatly appreciate a >>> "idiot-proof" response, I.e how should the data be entered into R? I was >>> thinking of using read.table, header = T, where the table has F = Family >>> Name, and SP = Number of species in that family? >>> >>> John >>> >>> ______________________________________________ >>> R-help@r-project.org mailing list >>> https://stat.ethz.ch/mailman/listinfo/r-help >>> PLEASE do read the posting guide >>> http://www.R-project.org/posting-guide.html >>> and provide commented, minimal, self-contained, reproducible code. >>> >> >> [[alternative HTML version deleted]] >> >> ______________________________________________ >> R-help@r-project.org mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. >> >> ______________________________________________ >> R-help@r-project.org mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. >> > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.