similar to: implementation of split or two-piece normal distribution?

dear all, here's a couple of questions that puzzled me in these last hours: ##### issue 1 qnorm(1-10e-100)!=qnorm(10e-100) qnorm(1-1e-10) == -qnorm(1e-10) # turns on to be FALSE. Ok I'm not a computer scientist but, # but I had a look at the R inferno so I write: all.equal(qnorm(1-1e-10) , -qnorm(1e-10)) # which turns TRUE, as one would expect, but all.equal(qnorm(1-1e-100) ,

Hello, for a frequency modelling problem I want to combine expert knowledge with incoming real-life data (which is not available up to now). The frequency has to be modelled with a poisson distribution. The parameter lambda has to be normal distributed (for certain reasons we did not NOT choose gamma althoug it would make everything easier). I've started with the subsequent two functions to

Hi, Having a weird problem with the integrate function. I have a function which calculates a loss density: I'd like to integrate it to get the distribution. The loss density function is: lossdensity<-function(p,Beta,R=0.4){ # the second derivative of the PDF # p is the default probability of the pool at which we are evaluating the lossdensity # Beta is the correlation with the market

Dear all, Suppose I plot two normal distributions (A and B) side by side and add vertical line which hipotheticaly represent alpha value; e.g.: x <- seq(-3.5,5, length=1000) y <- dnorm(x) # Plot distribution A plot(y~x, type='l',axes=F,xlab="",ylab="",lwd=2) # Plot distribution B y2 <- dnorm(x-1.5) lines(y2~x,lwd=2) # Plot vertical line for alpha value

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:

Hi, Am not sure if my code itself is correct. Here's what am trying to do: Minimize integration of a function of gaussian distributed variable 'x' over the interval qnorm(0.999) to Inf by changing value of parameter 'mu'. mu is the shift in mean of 'x'. Code: # x follows gaussian distribution # fx2 to be minimized by changing values of mu # integration to be done over

Hello If i want to resampl from the tails of normal distribution , are these commans equivelant??   upper tail:qnorm(runif(n,pnorm(b),1))  if b is an upper tail boundary   or   upper tail:qnorm((1-p)+p(runif(n))  if p is the probability of each interval (the observatins are divided to intervals)   Regards [[alternative HTML version deleted]]

Hi everyone, I am using R 2.4.1 on a MacOS X ("Tiger") operating system. In the last few day I was trying to estimate the parameters of a mixture of two normal distributions using Maximum Likelihood. The code is from Modern Applied Statistics with S (4th edition), chapter 16 ("Optimization"), the dataset is available under MASS in R. Unfortunately, when I tried out the

Hello, could You please help: I am looking for a way to formulate test accuracy measures such as test sensitivity, specificity, predictive values, and correct classification rate using p/d/qnorm. The tests' primary values follow a bimodal distribution, which is modelled by a mixture of two normal distributions: p * dnorm ((x - u1) / s1) / s1 + (1 - p) * dnorm ((x - u2) / s2) / s2)

Dear R helper, I hope that u can help me to sort out my problem because I sent an E-mail last night to R-list but I have not receive any help and at the same time I think this problem is not so hard. I have used the following functions before > K<-10 > prime<-c(2,3,5,7,11,13,17) > UN<-seq(1:K)%*%t(sqrt(prime)) > U1<-UN-as.integer(UN) > U<-matrix(qnorm(U1),K,7)

Hi everyone, I am new to R, but it's really great and helped me a lot! But now I have 2 questions. It would be great, if someone can help me: 1. I want to integrate a normal distribution, given a median and sd. The integrate function works great BUT the first argument has to be a function so I do integrate(dnorm,0,1) and it works with standard m. and sd. But I have the m and sd given.

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

This is probably embarrassingly basic, but I have spent quite a few hours in Google and RSeek without getting a clue - probably I'm asking the wrong questions... There is this guy who has decided to walk through Australia, a total distance of 4000 km. His daily portion (mean) is 40km with an sd of 10 km. I want to calculate the number of days it takes to arrive with 80, 90, 95, 99%

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

Hi everyone. My problem: I've 4 distributions: A, B, C and D: #A mA=16.6 sA=3.0 #B mB=18.9 sB=3.2 #C mC=20.3 sC=2.1 #D mD=24 sD=0.8 ###Graphiques ensembles plot(function(x) dnorm(x,mA,sA),0,40,col="orange",ylim=c(0,0.5)) plot(function(x) dnorm(x,mB,sB),0,40,add=T,col="green") plot(function(x) dnorm(x,mC,sC),0,40,add=T,col="blue")

Hi, Does anyone know what the distribution for the product of two correlated normal? Say I have X~N(a, \sigma1^2) and Y~N(b, \sigma2^2), and the \rou(X,Y) is not equal to 0, I want to know the pdf or cdf of XY. Thanks a lot in advance. yu [[alternative HTML version deleted]]

Hello everyone, I have a question about integration of two density function Intuitively, I think the value after integration should be 1, but they are not. Am I missing something here ? > t=function(y){dnorm(y, mean=3)*dnorm(y/2, mean=1.5)} > integrate(t, -Inf, Inf) 0.3568248 with absolute error < 4.9e-06 Also, is there any R function or package could do multivariate integration ?

Dear All I am trying to find a uniroot of a function within another function (see example) but I am getting an error message (f()values at end points not of opposite sign). I was wondering if you would be able to advise how redefine my function so that I can find the solution. In short my first function calculates the intergrale which is function of "t" , I need to find the uniroot of

(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, In R, qnorm is the inversion function of pnorm. (c.d.f) But there is no inversion function for dnorm. (p.d.f). Is there any easy (and quick) way to compute the inversion function of p.d.f in R ? Thanks ...