search for: wnv

...ters. I am using the ode() function (deSolve package) to run the numerical simulation and apply() to run the simulation function for each set of parameter values. I am having trouble getting the apply() function to work. Here is an example. Consider an epidemiology model of West Nile Virus: wnv.model <- function(Time, State, Pars){ with(as.list(c(State, Pars)), { dSB <- -(alphaB*betaB*SB*IM)/(SB + IB) dIB <- (alphaB*betaB*SB*IM)/(SB + IB) - deltaB*IB dSM <- bM*(SM + EM + IM) - (alphaM*betaB*IB*SM...

...g a model for enumerated datatypes > > Hi, > > I have used the scan() function to read data from a file as follows: > > x <- scan("myfile", as.list(c(rep("", times = 9), class="", rep("", times > = 3))), comment.char="") [WNV] How about taking it in easily understood stages? what <- as.list(rep("", 13)) names(what)[10] <- "Class" # Note 'class' is not a really good name to choose. x <- data.frame(scan("myfile", what = what)) > This reads in all the 13 fields. The...

Hi, Given that R reports Type I sums of squares, isn't it a bit anachronistic that it re-orders terms in formulae? > d <- expand.grid(y=rnorm(8), + A=factor(c(1,2)), + B=factor(c(1,2)), + C=factor(c(1,2))) > summary(aov(y ~ A+B+A:B+C,data=d)) Df Sum Sq Mean Sq F value Pr(>F) A 1 8.294e-34 8.294e-34 1.027e-33 1

I have a statistical problem which has given me no end of grief recently, and am posting here in the hope that somebody can give me a straight answer. I'm a IT postgrad, not a statistician, so people may have to speak really slowly and clearly for me to get it :) I am collecting simulation data, and the results are geometrically distributed (or approximately so). From what I can gather

I have 20 variables: 5,9,6,1,5,9,7,4,5,6,3,2,4,8,9,6,1,8,4,8 How do I calculate the corresponding quantiles from a normal distribution with the same mean and variance as the sample? Also, how do I draw a QQ plot of the data? Thanks for any help! -- View this message in context: http://www.nabble.com/Quantiles-and-QQ-plots-tf4925742.html#a14097909 Sent from the R help mailing list archive at

Hello, after searching through the archives and not finding a thread that answers this question, I thought I'd pass it on to the list. Given a data frame and given a factor variable that assigns a class to each case in the data frame, what is the most efficient way to sample a given number of cases from each class? I've found a roundabout solution that works as follows: for each class:

I came across a very cheap of the infamous blue book - The New S Language (1988). Is this book still relevant to modern S or R or am I wasting my time? -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the

In Mathematica there is a neat feature, where you can change the head of a list from "list" to say "+" and obtain a sum of the list elements. I can't find a way to sum a list of vectors of same length or list of matrices of the same dimension and was curious if something like that exists in R. do.call("+",list) doesn't work because "+" accepts only

Hello. I want to use "for". I have a matrix called "mat" that has got 100 rows. I want to take the line 1 and make a1<-which(mat[1,]==1) After this I want to take the second row and make a2<-which(mat[2,]==1) and so on until I arrive at row 100. I want to make it automatic for the 100 rows and so I wrote: for(i in 1:nrow(mat)){ ai<-which(mat[i,]==1) }

Dear R-helpers, Im trying to fit a Log-linear model on a dataset with bird counts from 60 sites over 14 years for 12 months each (factors for the models). One of the aims is to predict the missing values in this dataset with model predictions. Ive first tried to work with GLM's, that worked fine except for models with one or more interaction-terms. The GLMs run, run .. for hours. So I

Dear all, I want to evaluate several generalized linear mixed models, including the null model, and select the best approximating one. I have tried glmmPQL (MASS library) and GLMM (lme4) to fit the models. Both result in similar parameter estimates but fairly different likelihood estimates. My questions: 1- Is it correct to calculate AIC for comparing my models, given that they use

Hi Folks, I note that, while the "chisq" functions dchisq(x, df, ncp=0, log = FALSE) pchisq(q, df, ncp=0, lower.tail = TRUE, log.p = FALSE) qchisq(p, df, ncp=0, lower.tail = TRUE, log.p = FALSE) rchisq(n, df, ncp=0) all have a slot for the non-centrality parameter "ncp", of the functions for the t and F distributions: dt(x, df, log = FALSE)

I've got a data frame that looks like this: subject foo bar 2 1.7 3.2 2 2.3 4.1 3 7.6 2.3 3 7.1 3.3 3 7.3 2.3 3 7.4 1.3 5 6.2 6.1 5 3.4 6.9 ... That is, I've got multiple rows per subject. I need to compute summaries within categories where the subject has the same number

I'm trying to fit a simple linear regression of just Y ~ X, but both X and Y are noisy. Thus instead of fitting a standard linear model minimizing vertical residuals, I would like to minimize orthogonal/perpendicular residuals. I have tried searching the R-packages, but have not found anything that seems suitable. I'm not sure what these types of residuals are typically called

Peter Dalgaard writes: > Bill.Venables at cmis.csiro.au writes: > ........ > > [WNV] Now there's an insight! In fact I think that once you get used to > > the style you get to appreciate it. The commercial world substitutes > > politeness for candour. True candour can be disconcerting but it does get > > the message across much quicker. > Also, this...

To anyone who can help: I am trying to do an analysis of variance with a very unbalanced design and a few empty cells. How do I get R to use type III and more importantly type IV sums of squares? Thanks Deven Hamilton Department of Sociology University of Washington

I want to superimpose histograms from three populations onto the same graph, changing the shading of the bars for each population. After consulting the help files and the archives I cannot find out how to do this (seemly) simple graph. To be clear, I want - a single x axis (from -3 to 18) - three groups of bars forming the histograms of each population (they will not overlap much, but this is

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Hey, all Do you how to calculate the trigamma function, that is d**2(log(gamma(x))) / dx**2. The second-order derivative of log(Gamma(x))? I cannot find it in the R package, and somebody knows who or where to get such one? Thanks. Fred -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html

Hello ALL: How do I get R to list all possible orderings of 2 x's and 3 y's? It should look like this (which rows appear first is unimportant): x x y y y x y x y y x y y x y x y y y x y x x y y y x y x y y x y y x y y x x y y y x y x y y y x x Thanks, ANDREW