similar to: How to fix it?

I have an array of probabilities....it is p. So if user types x=1 then probability is p1=1/10. If user types x=2 it means that p2= p1+p2 if user types x=3 it means that p3=p1+p2+p3....and so on. So i created a code..... but it doesnt work properly. Help me plz to fix it) Thank u in advance. psidp=function(x){ p<-(1/10 2/5 2/5 2/5 2/5 1/10 1/10 1/10 1/10 1/10) i==0; if (x!=0){ for

I'm not sure I'm barking up the right tree here, but would I need to make use of groups to plot two separate datasets within ONE panel in xyplot? The desired end result is a single xy plot of two separate (but similar in values and ranges). Full code follows, xyplot code at bottom #########Determine Frequencies ##########coastal_slope #needs the maptools package to read ESRI grid

User has to type (input) x. After input....code has to check X with statement if There is a statement IF. If X=0 then Y=5/2 else =7; How to code it please. I tried but my code does not work ;( I wanna see how it looks like( thank u in advance( -- View this message in context: http://r.789695.n4.nabble.com/Help-me-please-to-code-tp4646932.html Sent from the R help mailing list archive at

I wanna generate random numbers from a vector... for example number<-c(0,1,3,4,5,6,8) so rsidp<-function(x){ i=0 for (i in seq(1:x)) {y<-sample(number,x, replace=T)} return(y) } so all random numbers have to be from vector "number"; so if I type rsidp(5)..... it has to give me 5 random numbers except 2,7,9 (because they are not in the vector "numbers"). help

I am a beginner in programmin in general and R specifically. I would like to generate a set of random numbers in a normal distribution but to limit the decimal places in these numbers to only 2. I have been using x1 <- runif(1,0,1) to generate my numbers. Can I add something to it to enable me to only get results rounded off to 6 decimal places? -- View this message in context:

Plz help me ;(( I lost 7 hours for thinking and doing this code ;( I need to create points.....20 points(dots). All these dots have to be in one graph... when i run this code....it gives me only one dote..... number<- (0,2,3,4,5,6,8) for (i in seq(1:20)) {rsidpVector=rsidp(i) mean(rsidpVector) plot (length(rsidpVector), mean(rsidpVector), ylab="sample mean", xlab= "sample

number<-c(0,1,3,4,5,6,8) rsidp<-function(x){ i=0 {y<-sample(number,x,replace=TRUE)} return(y) } plot(o, xlim=c(0,20), ylim(0,20), type="n", xlab="Sample size", ylab="Sample variance") for (i in seq(1:20)){ retVal=rsidp(i) var(rsidpVector) points (i, var(rsidpVector),pch=i,col=i) } -- View this message in context:

I tried lrm in library(Design) but there is always some error message. Is this function really doing the weighted logistic regression as maximizing the following likelihood: \sum w_i*(y_i*\beta*x_i-log(1+exp(\beta*x_i))) Does anybody know a better way to fit this kind of model in R? FYI: one example of getting error message is like: > x=runif(10,0,3) > y=c(rep(0,5),rep(1,5)) >

I'm trying to label axes using 'expression', but I would also like to change the font to Times New Roman (a requirement of the journal). I'd appreciate any advice. Here's one example of several things that I've tried, including changes to par() parameters 'family', 'font', 'font.axis', and 'font.lab', which are not shown below. x <- 1:10

Hi, I have the following code from Splus that I'd like to migrate to R. So far, the only problem is the arima.filt function. This function allows me to filter an existing time-series through a previously estimated arima model, and obtain the residuals for further use. Here's the Splus code: # x is the estimation time series, new.infl is a timeseries that contains new information # a.mle

Hi , R is a new language for me so sorry in advance if this error is to basic for posting. I have tried the R manual and search online for quite a few, if anyone could help i would be very thankful. Here is my code. kappa = 1.1 theta = 0.1 sigma = 0.4 rho = -0.6 v0 = 0.2 r = 0.05 T = 0.5 s0 = 1 K = 0.5 type = 1 Hestoncall = function(kappa,theta,sigma,rho,v0,r,T,s0,K,type) { u = 0.5 b

Hi R users I like to generate a certain type of matrix. If there are 10 variables, the matrix will have nrow=10, ncol=((10/2))/5+1. so the resulting matrix's dimension 10 by 2. If there are 50 variables the dimension of the resulting matrix will be 50 by 6. The arrangement of elements of this matrix is important to me and I can't figure out how to arrange elements. If I have 20

I got a vector of probabilities like, probs<-c(0.001,0.5,0.02,1,.....) Is there any nice and easy builtin function to get the number of occurences within some specified probabality range. Like with 2% it would be occur[1] = sum(probs[probs>0&probs<0.02]) occur[2] = sum(probs[probs>0.02&probs<0.04]) ... occur[50] =sum(probs[probs>0.09] & probs<1) (If it was a

Hi R users Here is what I got with help from Petr Pikal (Thanks Petr Pikal). I modified Petr Pikal's code to a little to meet my purpose. I created a function to generate a matrix generate.matrix<-function(n.variable) { mat<-matrix(0,n.variable,(n.variable/2)/5+1) #matrix of zeroes dd<-dim(mat) # actual dimensions mat[1:(dd[1]/2),1]<-1 #put 1 in first half of first column

Hi, I'm looking for an 8+ FXS ATA gateway (at least 8 ports but preferably at most 24 ports) with 2 ethernet interfaces for network/switch redundancy. So far I've only found the Grandstream GXW4008. I've searched similar brands such as Linksys and higher-end brands such as Quintum, but they all seem to have just one NIC. So, if the switch the ATA is connected to fails then I'm

Hi, We are looking towards a 8+ CO line setup (20 extensions) in our office but we do not want an IVR(auto-attendant) feature. All incoming will be answered by a receptionist. I have read the multi-line configuration for cisco 7960 thread in this list but that way I believe we could only display 6 incoming lines. What will happen to the rest? Does the expansion module for the cisco 7960 work

Hi, I have: a <- matrix(c(0,1,0,1),nrow=2) b <- matrix(c(1,1,1,0,0,0),nrow=3) c <- 1 d <- c(1,0,1) And I would like to join them in an object 'thing' so that I can access a, b, c, or d through an index in a for loop. For example: thing[4] would return [1] 1 0 1 Note however, that I have many of these 'thing' components. So many that a command like thing

I am running lrm() with a single factor. I then run anova() on the fitted model to obtain a p-value associated with having that factor in the model. I am noticing that the "Model L.R." in the lrm results is almost the same as the "Chi-Square" in the anova results, but not quite; the latter value is always slightly smaller. anova() calculates the p-value based on

Dovecot-2.2.1 allows empty messages to be APPENDed when using CATENATE: b1 append inbox catenate (text {0+} ) b1 OK [APPENDUID 1366726248 12] Append completed. Contrast this with regular APPEND: b2 append inbox {0+} b2 NO Can't save a zero byte message. Note that zero-size literals are OK but zero-size messages are not. So while "b1" above should fail like "b2",

Full_Name: Jari Oksanen Version: 2.6.2 RC (2008-02-07 r44369) OS: Linux Submission from: (NULL) (130.231.102.145) Even if function xspline() is called with argument draw=FALSE, it requires a graphics device (that it won't use since it was draw=FALSE). I run into this because I intended to use xspline within a function (that does not yet draw: there is plot method for that), and the function