similar to: Help with Integration Output

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 Can we get the result of an intigration without the absolute error? for example f1<-function(x1){(1/gamma(alpha))*x1^(alpha-1)*exp(-x1)*log(x1)} I1<-integrate(f1, 0, (max(cc)-tau1+(theta2/theta1)*tau1)/theta2) I1 0.08007414 with absolute error < 7.2e-05 I need the answer 0.08007414 withou the other part(with absolute error <7.2e-05) how can we do that? thank you and take care

Hi all, I want to add the red color under the standard normal curve to the right of 1.96. Can anyone give me a hand? Please see the code below. Thank you. x <- seq(-4, 4, length=100) hx <- dnorm(x) par(pty="s") plot(x, hx, type="l", xlab="z value", ylab="Density", main="density of N(0,1)") abline(v=1.96, col="red")

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?

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

Greetings: I would like comments on this example and after fixing it up, I need help from someone who has access to insert this in R's help page for plotmath. I uploaded a drawing http://pj.freefaculty.org/R/Normal-2009.pdf that is created by the following code http://pj.freefaculty.org/R/Normal1_2009_plotmathExample.R This will be a good addition to the plotmath help page/example.

Dear R Users on a self-written function for calculating maximum likelihood probability (plz check function code at the bottom of this message), one value, wden, suddenly jump to zero. detail info as following: w[11]=2.14 lnw =2.37 2.90 3.76 ... regw =1.96 1.77 1.82 .... wden=0.182 0.178 0.179... w[11]=2.14 lnw=2.37 2.90 3.76 ... regw =1.96 1.77 1.82 .... wden=0.182

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

Hello, When using bargraph.CI in package sciplot can the bars for each group be different colors? How do I select the color for each group? When I use this instead of the default (SD vs SE): bargraph.CI(x.factor = dose, response = len, data = ToothGrowth, ci.fun= function(x) c(mean(x)-sd(x), mean(x) + sd(x)) ) Am I getting 95% CI bars? Thank you kindly, Michael Just

I want to shade the area under the curve of the standard normal density. Specifically color to the left of -2 and on. How might i go about doing this? Thanks -- View this message in context: http://n4.nabble.com/Shade-area-under-curve-tp1586439p1586439.html Sent from the R help mailing list archive at Nabble.com.

Hi, Im very new in Ruby on Rails. I have to do intergrate jasper report with Rails applications. I found the link http://wiki.rubyonrails.org/rails/pages/HowtoIntegrateJasperReports. But Im not clear how to do. Plz help me this how to do. If anybody have sample application it will be very better. I look forward your reply... Thanks Velu

Hi, I am currently doing logistic regression analyses and I am trying to get confidence intervals for my partial logistic regression coefficients. Supposing I am right in assuming that the formula to estimate a 95% CI for a log odds coefficient is the following: log odds - 1.96*SE to log odds + 1.96*SE then I am not getting the right CI. For instance, this is a summary of my model:

a closer look to the help on predict.glm will reveal that the function accepts a 'type' argument. In you case 'type = response' will give you the results in probabilities (that it seems to be what you are looking for). There also is an example on use of the 'type' argument at the end of the page. Stefano -----Messaggio originale----- Da: r-help-bounces at r-project.org

I am very new to R and I basically used SPSS to do my model selection, which I had used generalized linear model. So my best model is P= D + T + L + T*L and there is a parameters table from the SPSS output which I suppose I have to use the coefficients (column B) in the table (as attached) when I draw my graph in R. I want to draw a graph in R which x-axis is D, using the model and the relevant

Is there an easy way to make the error bars the same color as the points and lines they are plotted with. My example # fake data x=sample(1:10, 100, replace =T) y = rnorm(100) + runif(100) df=data.frame(x,y) # summarize data m = aggregate(df,list(x),mean) se = aggregate(df,list(x),sd)/sqrt(10) library(Hmisc) plot(x,y) errbar(m$x, m$y, m$y+1.96*se$y,

hi all... anyone using mcafee antivirus with there samba server ? just wanted your comments, suggestions.... how did you intergrate it into samba ?

Dear all,I am a new user of WinBUGS and need your help. After running the following code, I got parameters of beta0 through beta4 (stats, density), but I don't know how to get the prediction of the last value of h, the variable I set to NA and want to model it using the following code.Does anyone can given me a hint? Any advice would be greatly appreciated.Best

How can I use row.names() as y-labels in Dotplot? How to set horizontal orientation for y-lables in lattice()? Dotplot(stcod1 ~ Cbind(statgh2,statgh2-1.96*segh2,statgh2+1.96*segh2)[og], subset=statgh2[og]>0.1, data=h2inqerrg02st, xlab="G", ylab=row.names(h2inqerrg02st)[og], main="") I have tried doing it with mtext() as well, but there is not enough space besides

Hi, ive walked into a enviroment where the previous admin has being using pop and making the email clients leaving a copy of the mail on the workstation.. Now overtime these mailboxes (mbox format) have grown between 1,5 to 1,8 Gigs large I want to convert all these mailbox to IMAP (only 15) and want to know whats the largested suggest folder size per user dovecot IMAP runs smoothly with

thanks a lot Renaud. but i was interested in Finney's fiducial confidence intervals of LD50 so to obtain comparable results with SPSS. But your reply leads me to the next question: does anybody know what is the best method (asymptotic, bootstrap etc.) for calculating confidence intervals of LD50? i could "get rid" of Finney's fiducial confidence intervals but