similar to: Integral of function of dnorm

The integral of any probability density from -Inf to Inf should equal 1, correct? I don't understand last result below. > integrate(function(x) dnorm(x, 0,1), -Inf, Inf) 1 with absolute error < 9.4e-05 > integrate(function(x) dnorm(x, 100,10), -Inf, Inf) 1 with absolute error < 0.00012 > integrate(function(x) dnorm(x, 500,50), -Inf, Inf) 8.410947e-11 with absolute error <

Dear all, does anybody ever encountered the problem with diagnostic plots? x<-rnorm(100) y<-rnorm(100) plot(lm(x~y)) It gives the following message "Waiting to confirm page change..." and nothing happens. Thanks a lot! [[alternative HTML version deleted]]

Dear all, Does anybody know the probable reason why <= gives false when it should give true? These two variables are of the same type, and everything works in the cycle but then it stops when they are equal. this is the output result > Rk[47] <= RB[21] [1] FALSE > Rk[47] [1] 0.002842007 > RB[21] [1] 0.002842007 Thanks a lot. [[alternative HTML version deleted]]

Dear all, might seem and easy question but I cannot figure it out. floor(100*(.58)) [1] 57 where is the trick here? And how can I end up with the right answer? Thanks a lot everybody for your help. Trafim [[alternative HTML version deleted]]

Hi all, I have some some problem with regard to finding the integral of a function containing an indicator function. please see the code below: func1 <- function(x, mu){ (mu^2)*dnorm(x, mean = mu, sd = 1)*dgamma(x, shape=2)} m1star <- function(x){ integrate(func1, lower = 0, upper = Inf,x)$val} T <- function(x){ 0.3*dnorm(x)/(0.3*dnorm(x)+0.7*m1star(x))} func2 <-

Dear all, Are there any functions in R to reverse the order of the string. smth like reverse("abc") to get "cba"? Thanks a lot. [[alternative HTML version deleted]]

Hi all, I have some some problem with regard to finding the integral of a function containing an indicator function. please see the code below: func1 <- function(x, mu){ (mu^2)*dnorm(x, mean = mu, sd = 1)*dgamma(x, shape=2)} m1star <- function(x){ integrate(func1, lower = 0, upper = Inf,x)$val} T <- function(x){ 0.3*dnorm(x)/(0.3*dnorm(x)+0.7*m1star(x))} func2 <-

Dear all, I have a question is there a possibility to plot points with different symbols like stars, crosses? I looked at different types for plot command and didn't find anything like that. Thanks a lot. [[alternative HTML version deleted]]

Hi all my apologies if above title is misleading, but here is my problem anyways: I need to evaluate an integral n times. Since I can't get my head around vectorization as of yet, I have coded it up in a loop, i.e.: for (i in 1:n) { z[i] <- integrate(dnorm,x[i],Inf) } Since n is quite large in my operation, ~40000, I would rather stack all the elements of x into a vector and

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

Dear all, I would like to ask you if there is a possibility in R to give the names to graphs which are not const. For example, How to name each plot, or to add notes like a=x[i], b=y[i] in this cycle x<-c(1,2,3,4,5,6) y<-c(7,8,9,10,11,12) par(mfrow=c(2,3)) for (i in 1:6){ plot(x,y) } Thank you for your time and help! [[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;

When I run the following function HQ2 <- function(n) { nv <- 6 * sqrt(n) fcn <- function(z) { pchisq(z^2 / 36, n - 1) * dnorm(nv - z) } ## I want the integral from 0 to infinity: f.Inf <- integrate(fcn, 0, Inf) ## Doc: "Don't do this": f.100 <- integrate(fcn, 0, 100) cbind(f.Inf, f.100) } I get, for n = 9 and

Dear all, I would like to ask how to extract the p-value for the whole model from summary(lm). This didn't help a lot summary.lm summary(lm(speed~dist, cars)) Thanks a lot! [[alternative HTML version deleted]]

Dear all, I cannot find to explicitly get the R-squared or adjusted R-squared from summary(lm()) Thanks a lot! [[alternative HTML version deleted]]

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

Dear all, does anyone know how to define the structure of the required samples using function createDataPartition, meaning proportions of different types of variable in the partition? Smth like this for iris data: createDataPartition(y = c(setosa = .5, virginica = .3, versicolor = .2), times = 10, p = .7, list = FALSE) Thanks a lot for your help. Regards, Trafim [[alternative HTML version

Hi, I'm trying to calculate the value of the variable, dp, below, in the argument to the integral of dnorm(x-dp) * pnorm(x)^(m-1). This corresponds to the estimate of the sensitivity of an observer in an m-alternative forced choice experiment, given the probability of a correct response, Pc, a Gaussian assumption for the noise and no bias. The function that I wrote below gives me an error:

Hi all, Is there any other packages to do numerical integration other than the default 'integrate'? Basically, I am integrating: integrate(function(x) dnorm(x,mu,sigma)/(1+exp(-x)),-Inf,Inf)$value The integration is ok provided sigma is >0. However, when mu=-1.645074 and sigma=17535.26 It stopped working. On the other hand, Maple gives me a value of 0.5005299403. It is an

Hi all, myint=function(mu,sigma){ integrate(function(x) dnorm(x,mu,sigma)/(1+exp(-x)),-Inf,Inf)$value } mymu=seq(-3,3,length(1000)) mysigma=seq(0,1,length(500))[-1] k=1 v=c() for (j in 1:length(mymu)) { for (i in 1:length(mysigma)) { v[k]=myint(mymu[j],mysigma[i]) k=k+1 } } Basically, I want to investigate for what values of mu and sigma, the integral is divergent. Is there another way