similar to: infinity in integrate function in R

Hi, I already found a conversation on the integration of a normal distribution and two suggested solutions (https://stat.ethz.ch/pipermail/r-help/2007-January/124008.html): 1) integrate(dnorm, 0,1, mean = 0, sd = 1.2) and 2) pnorm(1, mean = 0, sd = 1.2) - pnorm(0, mean = 0, sd = 1.2) where the pnorm-approach is supposed to be faster and with higher precision. I want to integrate a mixed

Dear R people The function below should be decreasing, convex, and tend to zero when x tends to infinity. curve((1-pnorm(x))/dnorm(x),from=0, to=9) >From the plot we see that for x between 8.0 and 8.3 the function is fluctuating. As far as I understand, this is due to the function pnorm() not being sufficiently accurate in the tails. I am using pnorm() in a way that has probably not been

Hi all, The function h below is a function of c and it should be a monotone increasing function since the integrand is nonnegative and integral is taken from c to infinity. However, as we can see from the plot, it is not shown to be monotone. Something wrong with the usage of integrate function? Thanks so much for your help. Hanna h <- function(c){ g <- function(x){pnorm(x-8.8,

> version _ platform i686-pc-linux-gnu arch i686 os linux-gnu system i686, linux-gnu status major 1 minor 7.1 year 2003 month 06 day 16 language R Bug: integrate(f,lower,upper,extra_args) where f <- function(x,extra_args) { body } integrate doesn't pass the extra arguments when calling f. As a first check of this finding I integrated dnorm from

Sorry. I meant in the previous email that the function h() is a monotone decreasing function. Thanks very much. 2018-02-06 13:32 GMT-05:00 li li <hannah.hlx at gmail.com>: > Hi all, > The function h below is a function of c and it should be a monotone > increasing function since the integrand is nonnegative and integral is > taken from c to infinity. However, as we can see

Hi Hanna, your function is essentially zero outside a short interval around 9. And the help page states: "If the function is approximately constant (in particular, zero) over nearly all its range it is possible that the result and error estimate may be seriously wrong." You could try to integrate over a finite interval, say (7, 12). G?ran Brostr?m On 2018-02-06 19:40, li li wrote:

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:

Here's another example of my plotmath whipping boy, the Normal distribution. A colleague asks for a Normal plotted above a series of axes that represent various other distributions (T, etc). I want to use vectors of equations in plotmath to do this, but have run into trouble. Now I've isolated the problem down to a relatively small piece of working example code (below). If you would

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

I'm trying to provide different parameters to the integrate function for various probability functions. I'm using dnorm as the simplest example here. For instance integrate(dnorm, -1.96, 1.96) produces the correct answer for a normal distribution with mean 0 and standard deviation 1. I've tried two ways to use mean=2.0 and standard deviation 1, but with no luck. The examples follow.

Hi list. I''m writing a program that stores a lot of Floats into MySQL database. Simplified version of the program use the following form of class. class Val < ActiveRecord::BASE end And Vals table contains one column: num double One of my data contains -Infinity for num and when I try to Val.new Val.num = <- Here goes -Inifinity Val.save! Then the program crashes:

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

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

I'd like to be able to modify axlab in (C) below so that 'Inf' is replaced by the infinity symbol. y <- rnorm(40) breaks <- c(-Inf, -1, 1, Inf) x <- cut(y, breaks=breaks) plot(unclass(x), y, xaxt="n", xlab="") ## A: The following gives the axis labels "(-Inf, 1]", etc. axis(1, at=1:3, labels=expression("(-Inf,-1]", "(-1,1]",

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:

Dear R-people, I have to compute C - -(pnorm(B)*dnorm(B)*B + dnorm(B)^2)/pnorm(B)^2 This expression seems to be converging to -1 if B approaches to -Inf (although I am unable to prove it). R has no problems until B equals around -28 or less, where both numerator and denominator go to 0 and you get NaN. A simple workaround I did was C <- ifelse(B > -25, -(pnorm(B)*dnorm(B)*B

Dear list members, I'm quite new to R, and though I tried to find the answer to my probably very basic question through the available resources (website, mailing list archives, docs, google), I've not found it. If I try to use the "integrate" function from within my own functions, my functions seem to misbehave in some contexts. The following example is a bit silly, but

Hi, I have one basic doubt. Suppose X ~ N(50,10). I need to calculate Probability X = 50. dnorm(50, 50, 10) gives me [1] 0.03989423 My understanding is (which is bit statistical or may be mathematical) on a continuous scale, Probability of the type P(X = .....) are nothing but 1/Infinity i.e. = 0. So as per my understanding P(X = 50) should be 0, but even excel also gives 0.03989422. Obviously

Bug Using read.table(file, encoding="UTF-8") to import a UTF-8 encoded file containing the infinity symbol (' ? ') results in the infinity symbol imported as the number 8. Other Unicode characters seem unaffected, example, Zhe: ? Expected Behavior: The imported data.frame should represent the infinity symbol as the expected 'Inf' so that normal mathematical operations

I believe that this may be more appropriate here in r-devel than in r-help. The normal hazard function, or reciprocal Mill's Ratio, may be obtained in R as dnorm(z)/(1 - pnorm(z)) or, better, as dnorm(z)/pnorm(-z) for small values of z. The latter formula breaks dowm numerically for me (running R 2.4.1 under Windows XP 5.1 SP 2) for values of z near 37.4 or greater. Looking at the pnorm