similar to: Integrate(dnorm) with different mean and standard deviation help

Hi, I need to do a calculation in R which involves adding the estimate of a numerical integration with another number - however, if I add the number to the output of the intergrate function (which when run on its own provides me with a number with error), I get the message 'non-numeric argument to binary operator'. How would I be able to avoid this and use the estimate? eg: I have the

Full_Name: Marco Vezzoli Version: 2.2.0 2.1.0 2.0.0 OS: Solaris, Windows, Linux Submission from: (NULL) (57.78.11.38) The dnorm functions yield a wrong value when the standard deviation is near to 1e-1 e.g. > dnorm(0,mean=0.04,sd=0.3) [1] 1.318039 this error is consistent in various version and os.

Dear R community, I was trying to estimate density at point zero of a multivariate distribution (9 dimensions) and for this I was using a multinormal approximation and the function dmvnorm , gtools package. To have a sense of the error I tried to look the mismatch between a unidimensional version of my distribution and estimate density at point zero with function density, dmvnorm and dnorm. At

I am attempting to wrap the histogram function in my own custom function, so that I can quickly generate some standard plots. A part of what I want to do is to draw a normal curve over the histogram: > x <- rnorm(1000) > hist(x, freq=F) > curve(dnorm(x), lty=3, add=T) (for normal use, x would be a vector of empirical values, but the rnorm() function works for testing) That

Hello: The example "integrate(dnorm,0,20000)" says it "fails on many systems". I just got 0 from it, when I should have gotten either an error or something close to 0.5. I got this with R 2.12.0 under both Windows Vista_x64 and Linux (Fedora 13); see the results from Windows below. I thought you might want to know. Thanks for all your work in creating

sorry the integration was from -Inf to 1.96 The integrate function in R is not taking Inf (infinity). How do you use infinity in R. I was doing: integrate(dnorm,- Inf, 1.96) and I was getting Error: NA/NaN/Inf in foreign function call (arg 2). Obviously this should be equal to pnorm(1.96)= 0.9750021. How do you get around the infinity problem in R?

Howdee, One of my student spotted something I can't explain: a probability >1 vs a normal probability density function. > dnorm(x=1, mean=1, sd=0.4) [1] 0.9973557 > dnorm(x=1, mean=1, sd=0.39) [1] 1.022929 > dnorm(x=1, mean=1, sd=0.3) [1] 1.329808 > dnorm(x=1, mean=1, sd=0.1) [1] 3.989423 > dnorm(x=1, mean=1, sd=0.01) [1] 39.89423 > dnorm(x=1, mean=1, sd=0.001) [1]

#Quick one hopefully. Shouldn't dnorm be returning the pdf? Last time I checked, #a probability shouldn't be greater than 1 as produced by: curve(dnorm(x,0,.1),from=-1,to=t) #Shouldn't I be getting an axis more like that produced by: f=function(x,m,s){ y=rep(NA,length(x)) for(i in 1:length(x)){ y[i]=integrate( dnorm , upper=x[i]+sqrt(.Machine$double.eps) ,

Dear R-users Idea: Plot a dnorm line using specific mean/sd to complete a histogram (skewed). xs:range of y-values, ys: dnorm function Problem: I expected to multiply the ys function with the sample size (n=250-300). I was wondering about a factor between 12'000 and 30'000 to match the size of the dnorm line with the specific histogram. Thanks Sibylle hist(Biotree[Ld,]$Height2008,

Hello all, I have a question about basic statistics. Given a PDF value of 0.328161, how can I find out the value of -0.625 in R? It is like reversing the dnorm function but I do not know how to do it in R. > pdf.xb <- dnorm(-0.625) > pdf.xb [1] 0.328161 > qnorm(pdf.xb) [1] -0.444997 > pnorm(pdf.xb) [1] 0.628605 Many thanks, Edwin -- View this message in context:

Number of subjects = 25 Mean of Sample = 77 Standard Deviation (s) = 12 sem = 2.4 df = 24 The claim is that population mean is less than 80 * > 80 So our H0 (null hupotheis) is * > 80 > qt(.95,24) [1] 1.710882 > qt(0.05, 24) [1] -1.710882 tstat = -1.25 on t24 falls between 1.711 (.95,24) and *1.711 (.005,24) How Could I sketch t curve for the above data where my * would be at the

Hi All, Why would calls to dnorm and dmvnorm return values that are above 1? For example, > dnorm(0.00003,mean=0, sd=0.1) [1] 3.989423 This is happening on two different installations of R that I have. Thank you. Hailu [[alternative HTML version deleted]]

Hi, I have the following data about courses (504) in a university, two attributes about the proportion of resources used (#resources_used / #resources_available), namely the average and the standard deviation. Thus I have: [1] n=504 rows [2] 1 id column and 2 attributes Here's a sample of the data: courseid,average,std 12741,1,0 17161,1,0 12514,1,0

Hello, I am searching for a method to calculate a normal distribution. For example this equation is used to calculate the normal curve when the mean and standard deviation are know. p(x) = (1/?*sqrt(2?)) x exp (- (x-?)2/2?2) or (Embedded image moved to file: pic27350.jpg)Normal Probability Distribution Formula However, some of the literature I'm reading (I'm building an ecological

Hello, This must be really simple, but I can't find it on R Site search. I need to generate a random normally distributed series with mean 0 and sd 1. In Matlab, this code is randn(n). The closest I found is runif(20,-1,1) but this forces a maximum and a minimum, and there's no way to specify a standard deviation of 1. >sd(runif(20,-1,1)) [1] 0.578164

Hi, Apropos of a recent Inf question, I've previously wondered if dnorm "does the right thing" with dnorm(0, 0, -Inf) which gives zero. Should that be zero or NaN (or NA)? The help says "'sd < 0' is an error and returns 'NaN'" and since -Inf < 0 is TRUE, then... is this a bug? Thank you, Stephen Rochester, MN USA

Hi! I need to perform ANOVA on a couple of data sets. The only information I have are N, Mean and Standard deviation. I am very new to R, so can someone point me to the right direction on where to go? Thank you very much. Sincerely Niny Rao, PhD Philadelphia University

Dear all, How is it possible in R to calculate the following integral: Integral(-Inf, Inf)[log(dnorm(mean = 3, sd = 1))] how can I define that the density dnorm is taken on (-Inf, Inf) Thanks a lot! [[alternative HTML version deleted]]

Yes, that looks like a bug and an easily fixable one too. However, I spy another issue: Why do we check the !R_FINITE(x) && mu == x before checking for sd < 0 ? The difference is whether we return ML_NAN; or ML_ERR_return_NAN; but surely negative sd should always be an error? I'd be inclined to do if (sigma < 0) ML_ERR_return_NAN; if(!R_FINITE(sigma)) return R_D__0;

Dear R-experts! I am currently running a meta-analysis with the help of the great metafor package. However I have some difficulties setting up my raw data to enter it to the meta-analysis models. I have a group of subjects that have been measured in two continuous variables (A & B). I have the information about the mean of the two variables, the group size (n) and the standard deviations of