similar to: Confidence Intervals for Poisson

Here I am again with question I'll feel foolish for asking, when I see the answer. I'm trying to produce a report and here's where I get stuck: How do I get R2HTML to produce the same number format? Particularly remove the decimal places for Par and Sal. Are there better methods to produce this type of report? Thanks, L.A. R version 2.10.0 XP

Hi, R 1.0.1, on Linux(mandrake/RedHat). I am trying to write my first function using R and I need help figuring out the error I have indicated in the Subject line above. The purpose of the function is not to "wow" anyone, but just to serve as a stepping stone so that I might write more complicated functions in the future. First I created my function named "CIfunc" and saved

Another question about lattice: Is there a way to use plotmath in the labels and strips? E.g. xyplot(y~x|group,data=test.df, panel=function(x,y,subscripts,df) { llines(x,y,col="black",lwd=2) llines(x,df[subscripts,"lowerCI"],lty=2,col="#aaaaaa") llines(x,df[subscripts,"upperCI"],lty=2,col="#aaaaaa") },

Forwarded Message: > To: Steve Arthur <sarthur at crick.protogene.com> > From: Thomas Lumley <thomas at biostat.washington.edu> > Subject: Re: [R] couldn't find function "..." > Date: Wed, 5 Jul 2000 16:16:25 -0700 (PDT) > ----- > On Wed, 5 Jul 2000, Steve Arthur wrote: > > > Hi, > > > > R 1.0.1, on Linux(mandrake/RedHat).

R, I want to get means and confidence limits on the original scale for the treatment effect after running a mixed model. The data are: response<-c(16,4,5,8,41,45,10,15,11,3,1,64,41,23,18,16,10,22,2,3)

Full_Name: Manikandan Narayanan Version: 2.8.1 OS: Linux Submission from: (NULL) (155.91.45.231) Here is an excerpt from qpois help page (?qpois): The quantile is left continuous: 'qgeom(q, prob)' is the largest integer x such that P(X <= x) < q. I think the "qgeom" here should be "qpois" instead. Please correct this typo in ?qpois, since it's

Folks, I'm fairly sure that I'm doing something stupid, but I'm getting a few really strange results from *some* of the distributions, but by no means all, when I link directly to the R shared library. I've tried this on both Windows with the precompiled Mingw binary of R-2.5.0 (compiling my code with MinGW-3.4.2), and by building R-2.5.0 on Mandriva Linux with gcc-3.4.4 and

> How can I draw a Hypercube sample for the variable mortality_probability so > that this variable exhibits the same pattern as the observed distribution? One simple way is to use the uniform random output of randomLHS as input to the quantile function for your desired distribution(s). For example: q <- randomLHS(1000, 3) colnames(q) <- c("A", "B",

Thanks for your answer. However, my variable is simulated from the cumulative distribution function of the Poisson distribution. So, the pattern obtained from the function "qpois" is not the same as the observed pattern (i.e., obtained from the function "ppois") set.seed(5) mortality_probability <- round(ppois(seq(0, 7, by = 1), lambda = 0.9), 2)

Full_Name: Jerry W. Lewis Version: 2.10.1 OS: Windows XP Professional Submission from: (NULL) (198.180.131.21) In the line "The quantile is right continuous: qpois(q, lambda) is the smallest integer x such that P(X <= x) >= q." "q" is used as a probability when the Arguments section defines it to be a quantile. Also there are some representation problems where the

(1) ...need to speed up a monte-carlo sampling...any suggestions about how I can get R to use all 8 cores of a mac pro would be most useful and very appreciated... (2) spent the last few hours trying to get pnmath to compile under os- x 10.5.4... using gcc version 4.2.1 (Apple Inc. build 5553) as downloaded from CRAN, xcode 3.0... ...xcode 3.1 installed over top of above after

Hi all, why doesn't something like this does not work? speedy <- (sdata$VaR < sdata$DdtdAbs) && sdata$DdtdDuration >= qpois(pct,lambda) && sdata$Ddtd > MinDD or sdata$Ddtd[sdata$Ddtd > 0 && sdata$VaR < sdata$DdtdAbs] sdata looks like this: dataId date value Ddtd VaR DdtdAbs DdtdDuration 18948 79637 2004-07-27 10085.10

Could somebody help me to understand the syntax of R's ppois function? I'm looking to calculate the cumulative probability density of an observed value (y) given the expected mean (mu) and the level of significance (alpha). I'm coming from using SAS to do this and don't recognize the descriptions of the arguments for ppois. The definitions of lambda and p as stated in the R manuals

Full_Name: Mikael Weigelt Version: 2.0 OS: windows Submission from: (NULL) (207.171.180.101) The calculation of the qpois attempts to use the Cornish-Fisher expansion as a starting approximation. The definition of the expansion is incorrect. However, since this approximation just gives an initial solution, the end result of the function is still correct. To fix the approximation, in the

Hello, I am performing a sensitivity analysis using a Latin Hypercube sampling. However, I have difficulty to draw a Hypercube sample for one variable. I?ve generated this variable from a Poisson distribution as follows: set.seed(5) mortality_probability <- round(ppois(seq(0, 7, by = 1), lambda = 0.9), 2) barplot(mortality_probability, names.arg = seq(0, 7, by = 1), xlab = "Age

version .62: --------------------------------------------- > ?qpois The Poisson Distribution dpois(x, lambda) ppois(q, lambda) qpois(p, lambda) rpois(n, lambda) Arguments: x: vector of (positive) quantiles. p: vector of probabilities. n: number of random values to return. lambda: vector of positive means.

On a recent FreeBSD 8.0-CURRENT (i386) building R (any version) breaks with the following messages: ---------------------------------------------------------------------- [...snip...] gcc -std=gnu99 -I. -I../../src/include -I../../src/include -I/usr/local/include -DHAVE_CONFIG_H -g -O2 -c wilcox.c -o wilcox.o gcc -std=gnu99 -I. -I../../src/include -I../../src/include -I/usr/local/include

Hi I want to write a C function for the R Code below and call it with .Call: SimPoisson <- function(lambda,tgrid,T2M) #Simulation eines Poissonprozesses { NT <- 0 Ni <- rep(0,length(tgrid)) tau <- 0 sign <- 0 if(lambda != 0) { i=1 j=1 while (1) { EVar <- rexp(1,lambda) sign <- sign + EVar if (sign > T2M) { break } tau[i] <- sign

Full_Name: Wolfgang Resch Version: R 2.8.1 GUI 1.27 OS: OS X 10.4.11 Submission from: (NULL) (137.187.89.14) Strange behavior of qbinom: > qbinom(0.01, 5016279, 1e-07) [1] 0 > qbinom(0.01, 5016279, 2e-07) [1] 16 > qbinom(0.01, 5016279, 3e-07) [1] 16 > qbinom(0.01, 5016279, 4e-07) [1] 16 > qbinom(0.01, 5016279, 5e-07) [1] 0

I am interested in R functions for the following integrals / sums (expressed best I can in text) - Normal: G_u(k) = Integration_{Lower limit=k}^{Upper limit=infinity} [(u -k) f(u) d(u)], where where u is N(0,1), and f(u) is the density function. Poisson: G(lambda,k) = Sum_{Lower limit=k}^{Upper limit=infinity} [(x-k) p(x, lambda)] where P(x,lambda) is the Poisson prob function with parameter