search for: logk

I'm getting an error message when using the new version of sqldf, > library(sqldf) > str(kdv) 'data.frame': 71 obs. of 3 variables: $ dpss: num 0.117 0.144 0.164 0.166 0.165 ... $ npdp: num 0.1264 0.0325 0.0109 0.0033 0.0055 ... $ logk: num 1.12 1.29 1.41 1.41 1.42 ... > test=sqldf("select * from kdv") Error in get("fun", env = this, inherits = TRUE)(this, ...) : could not find function "combine" Anyone know how to fix this? Thank you Martin -- View this message in context: http://www.nabbl...

Hey, So I have a scatter plot and I am trying to plot a curve to fit the data based on a Holling Type III functional response. My function is this: nll2<-function(a,b) { conefun<-(a*DBH^2)/(b^2+DBH^2) nlls2<-dnbinom(x=cones ,size=DBH, mu=conefun,log=TRUE) -sum(nlls) } and my plot is this: plot (DBH,cones) DBH is on the x-axis and cones is on the y-axis. How do I get the curve

...gt; m.hi = m0 > else m.lo = m0 > if (abs(p0 - p) < 1e-04) > flag = 1 > } > return(m0) > } > p1 = quantile1$p > x1 = quantile1$x > p2 = quantile2$p > x2 = quantile2$x > logK = seq(-3, 8, length = 100) > K = exp(logK) > m = sapply(K, betaprior1, x1, p1) > prob2 = pbeta(x2, K * m, K * (1 - m)) > ind = ((prob2 > 0) & (prob2 < 1)) > app = approx(prob2[ind], logK[ind], p2) > K0 = exp(app$y) > m0 = betaprior1(K0, x1,...

Hi, I am trying to run a generalized linear regression using a negative binomial error distribution. However, I want to use an overdispersion parameter that varies (dependent on the length of a stretch of road) so glm.nb will not do. >From what I've read I should be able to do this using GLM by specifying my own quasi family and describing the variance function using varfun, validmu,

Dear Ben, you answerd to Nancy Shackelford about Clarks 2Dt function. Since the thread ended just after your reply, I would like to ask, if you have an idea how to use this function in R I defined it the following way: function(x , p, u) { (p/(pi*u))*(1+(x^2/u))^(p+1) } and would like to fit this one to my obeservational data (count) [,1] [,2] [1,] 15 12 [2,] 45 13 [3,]

Hi I'm trying to replicate Smith et al.'s (http://www.sciencemag.org/content/330/6008/1216.abstract) findings by fitting their Gompertz and logistic models to their data (given in their supplement). I'm doing this as I want to then apply the equations to my own data. Try as a might, I can't quite replicate them. Any thoughts why are much appreciated. I've tried contacting the

Hi there, I have been having trouble running negative binomial regression (glm.nb) using library MASS in R v2.15.0 on Mac OSX. I am running multiple models on the variables influencing the group size of damselfish in coral reefs (count data). For total group size and two of my species, glm.nb is working great to deal with overdispersion in my count data. For two of my species, I am getting a

...ething similar. I was told that with FreeBSD i was to use mount. But i have no idea what file type and what the options are. This isn't in any documentation i could find on samba.org. If someone could help me? Share Path : \\192.168.24.253\LogFiles$ Mount Path : /var/ServerLogs UserName: LogKing Password: goLgniK

...lt;- as.character(i) # convert to match the names(freq), the character-based hash key of freq, which is the value if (!(ichar %in% names(kfreq))) kfreq[ichar] <- 0 } sortedkeys <- as.character(k) kfreq <- kfreq[sortedkeys] pk <- kfreq / length(y) logk <- log(k) logpk <- log(pk) logpk[logpk == -Inf] = "" # remove the -Inf or log(p(k)) = 0 values for lm function, NULL is 0-length so use "" instead that has length of one null character logpk <- as.numeric(logpk) # "" converts all values to charact...

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