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I am using /set.seed()/ before the /sample/ function. How does the length of the argument of /set.seed()/ and order of the digits affect how the sampling is carried out? Specifically, I have used set.seed(123456789). Will this configuration give me a genuinely random sampling?? Thank you in anticipation. Penny. [[alternative HTML version deleted]]

I am trying to find a confidence band for a fitted non-linear curve. I see that the predict.nls function has an interval argument, but a previous post indicates that this argument has not been implemented. Is this still true? I have tried various ways to extract the interval information from the model object without success. My code is: Model.predict <- predict(My.nls.model,

I am having a slight problem with probabilities. To calculate the final probability of an event p(F), we can take the product of the chance that each independent event that makes p(F) will NOT occur. So... p(F) = 1- ( (1-p(A)) * (1-p(B)) * (1-p(C))...(1-p(x)) ) If the chance of an event within the product occurring remains the same, we can therefore raise this probability to a power of the

Hello fellow R users, I am having a problem finding the estimates for some overall treatment effects for my mixed models using 'lme' (package nlme). I hope someone can help. Firstly then, the model: The data: Plant biomass (log transformed) Fixed Factors: Treatment(x3 Dry, Wet, Control) Year(x8 2002-2009) Random Factors: 5 plots per treatment, 5 quadrats per plot (N=594 (3*5*5*8)

I have a problem related to measuring likelihood between -an observed presence absence dataset (containing 0 or 1) -a predicted simulation matrix of the same dimensions (containing values from 0 to 1) This must be a common problem but I am struggling to find the answer in the literature. Within the simulation model I have a parameter 'm' which I can alter to find the best fit (maximum