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...aquete "vegan", concretamente la función "metaMDS" y me gustaría saber si puedo usar más de un procesador a la vez para acelerar los cálculos. He visto el paquete "multicore" pero no sé usarlo, ¿alguien lo ha usado para algo así? Gracias y saludos, Javier -- http://oikos.inf.um.es

...on available in spatstat, but there doesn't not appear to be one for the pair-correlation function (O-ring statistic). As such I was planning to use a new technique (the K2 index) as described in Schiffers et al. (2008) [Ecography, 31:545-555]. The following website has more detail [http://www.oikos.ekol.lu.se/appendixdown/E5374-example.R]. Despite this I cannot get the function to run! I am not very familiar with R so it is likely my problem is simple. Does anyone have any experience with the K2-index who can give me some pointers? Many thanks Lauren This message has been checked for...

Rainer M Krug writes: > Thorsten Wiegand used in his paper Wiegand T., and K. A. Moloney 2004. > Rings, circles and null-models for point pattern analysis in ecology. > Oikos 104: 209-229 a statistic he called O-Ring statistic which is > similar to Ripley's K, only that it uses rings instead of circles. > > http://www.oesa.ufz.de/towi/towi_programita.html#ring > > Is this statistic included in one of the packages in R? This kind of functiona...

...artial correlation for wildlife census time series Dear List; We are doing a time series analysis of wildlife census data. We use a stepwise regression of the annual per capita rate of increase against pervious years population size (log transformed) as suggested by Berryman & Turchin (2001, Oikos 92:265-270). How can we obtain the partial correlation coefficients in R to make a plot of them against the lag as in a standard PACF? Yours Sincerely Tomas Willebrand

Hi I?m trying to fit a nonlinear model to a derivative of the logistic function y = a/(1+exp((b-x)/c)) (this is the parametrization for the SSlogis function with nls) The derivative calculated with D function is: > logis<- expression(a/(1+exp((b-x)/c))) > D(logis, "x") a * (exp((b - x)/c) * (1/c))/(1 + exp((b - x)/c))^2 So I enter this expression in the nls function:

Hi Thorsten Wiegand used in his paper Wiegand T., and K. A. Moloney 2004. Rings, circles and null-models for point pattern analysis in ecology. Oikos 104: 209-229 a statistic he called O-Ring statistic which is similar to Ripley's K, only that it uses rings instead of circles. http://www.oesa.ufz.de/towi/towi_programita.html#ring Is this statistic included in one of the packages in R? Thanks, Rainer -- Rainer M. Krug, Dipl. Phys. (Ger...

Hi all I?m trying to get confidence intervals for parameters from nls modeling. I fitted a nls model to the following variables: > x [1] 2 1 1 5 4 6 13 11 13 101 101 101 > y [1] 1.281055090 1.563609934 0.001570796 2.291579783 0.841891853 [6] 6.553951324 14.243274230 14.519899320 15.066473610 21.728809880 [11] 18.553054450 23.722637370 The model fitted was:

...uests are welcome! Khurram and Peter -- Khurram Nadeem knadeem at math.ualberta.ca University of Alberta P?ter S?lymos solymos at ualberta.ca University of Alberta References Nadeem, K. & Lele, S.R. 2012. Likelihood based population viability analysis in the presence of observation error. Oikos, early online Ponciano, J. M. et al. 2009. Hierarchical models in ecology: confidence intervals, hypothesis testing, and model selection using data cloning. Ecology 90: 356--362. Lele, S. R. et al. 2007. Data cloning: easy maximum likelihood estimation for complex ecological models using Bayesia...

...uests are welcome! Khurram and Peter -- Khurram Nadeem knadeem at math.ualberta.ca University of Alberta P?ter S?lymos solymos at ualberta.ca University of Alberta References Nadeem, K. & Lele, S.R. 2012. Likelihood based population viability analysis in the presence of observation error. Oikos, early online Ponciano, J. M. et al. 2009. Hierarchical models in ecology: confidence intervals, hypothesis testing, and model selection using data cloning. Ecology 90: 356--362. Lele, S. R. et al. 2007. Data cloning: easy maximum likelihood estimation for complex ecological models using Bayesia...

...signing = Auto guest account = nobody directory mask = 0770 unix charset = ISO8859-1 preferred master = yes set primary group script = /usr/sbin/smbldap-usermod -g "%g" "%u" printcap name = cups smb ports = 139 445 passwd program = /usr/local/sbin/smbldap-passwd %u workgroup = Oikos enable privileges = yes encrypt passwords = yes delete group script = /usr/sbin/smbldap-groupdel "%g" ldap user suffix = ou=People ldap admin dn = cn=admin,dc=duet,dc=it name resolve order = wins bcast ldap passwd sync = Yes add group script = /usr/sbin/smbldap-groupadd -p "%g&quot...

Hi all I have fitted a model usinf nls function to these data: > x [1] 1 0 0 4 3 5 12 10 12 100 100 100 > y [1] 1.281055090 1.563609934 0.001570796 2.291579783 0.841891853 [6] 6.553951324 14.243274230 14.519899320 15.066473610 21.728809880 [11] 18.553054450 23.722637370 The model fitted is: modellogis<-nls(y~SSlogis(x,a,b,c)) It runs OK. Then I calculate

Muy buenas, quiero calcular correlaciones de Pearson entre dos variables (a,b) teniendo en cuenta una tercera (c). Para ello estoy usando una función llamada "pcor.test" (http://www.yilab.gatech.edu/pcor.html), que en realidad no está en ningún paquete de R, que yo sepa. ¿Alguien conoce una función similar en alguna librería de R? Por otro lado, para ver si me cuadraban los resultados,

Hi all I?ve got a problem using boxcox.nls function in nlrwr packagge. I?m fitting several non linear models to these data: > x [1] 2 1 1 5 4 6 13 11 13 101 101 101 > y [1] 1.281055090 1.563609934 0.001570796 2.291579783 0.841891853 [6] 6.553951324 14.243274230 14.519899320 15.066473610 21.728809880 [11] 18.553054450 23.722637370 I used nls function with self

Hi all I?m trying to tests the significance of loadings from a ordination of 46 variables (caategorical, ordinal and nominal). I used dudi.mix from ade4 for the ordination. A years ago Jari Oksanen wrote this script implementing Peres-Neto et al. 2003 (Ecology) bootstraping method: netoboot <- function (x, permutations=1000, ...) { pcnull <- princomp(x, cor = TRUE, ...) res

Dear R users, I am using lme and nlme to account for spatially correlated errors as random effects. My basic question is about being able to correct F, p, R2 and parameters of models that do not take into account the nature of such errors using gls, glm or nlm and replace them for new F, p, R2 and parameters using lme and nlme as random effects. I am studying distribution patterns of 50 tree