search for: xnew

...Mxx*Myy - Mxy*Mxy; Mxz2 = Mxz*Mxz; Myz2 = Myz*Myz; A2 = 4*Cov_xy - 3*Mz*Mz - Mzz; A1 = Mzz*Mz + 4*Cov_xy*Mz - Mxz2 - Myz2 - Mz*Mz*Mz; A0 = Mxz2*Myy + Myz2*Mxx - Mzz*Cov_xy - 2*Mxz*Myz*Mxy + Mz*Mz*Cov_xy; A22 = A2 + A2; epsilon=1e-12; ynew=1e+20; IterMax=20; xnew = 0; # Newton's method starting at x=0 epsilon=1e-12; ynew=1e+20; IterMax=20; xnew = 0; iter=1:IterMax for (i in 1:IterMax){ yold = ynew; ynew = A0 + xnew*(A1 + xnew*(A2 + 4.*xnew*xnew)); if (abs(ynew) > abs(yold)){ print('...

...g is my "Iterator". When I try to write a new function with itel, I got error. This is what I have: > supDist<-function(x,y) return(max(abs(x-y))) > > myIterator <- function(xinit,f,data=NULL,eps=1e-6,itmax=5,verbose=FALSE) { + xold<-xinit + itel<-0 + repeat { + xnew<-f(xold,data) + if (verbose) { + cat( + "Iteration: ",formatC(itel,width=3, format="d"), + "xold: ",formatC(xold,digits=8,width=12,format="f"), + "xnew: ",formatC(xnew,digits=8,width=12,format="f"), + "\n&quot...

...rom lme4: lmerWrapper <- function(formula, data, family = gaussian, method = c("REML", "ML", "PQL", "Laplace", "AGQ"), control = list(), start = NULL, subset, weights, na.action, offset, contrasts = NULL, model = TRUE, ...) { xNew <- runif(0,1, length(data[,1])) fNew <- sample(1:4, length(data[,1]), replace = T) data <- as.data.frame(cbind(data, xNew, fNew)) formula <- update(formula, .~. + xNew + (1|fNew)) out <- lmer (formula = formula, data = data, family = family, method = method, w...

...quot;l"); lines(x, d$fitted.values, col="blue") # Fits great! all.equal(as.numeric(d$coefficients[1] + m %*% d$coefficients[2:5]), as.numeric(d$fitted.values)) What I would like to do now is to apply the estimated model to do prediction for a new set of x points e.g. xnew <- seq(0,5,.5) We know that the predicted values should be roughly sin(xnew). What I don't know is: how do I use the object `d' to make predictions for xnew? -- Ajay Shah http://www.mayin.org/ajayshah ajayshah at mayin.org...

Hi R users, I am a new user, still learning basics of R. Is there anyway to extract y (or x) value for a known x (or y) value from ecdf (empirical cumulative distribution function) curve? Thanks in advance. Mano. [[alternative HTML version deleted]]

...alues with the following headers: timeM1 statusM1 xM1 timeM2 statusM2 xM2 timeM3 statusM3 xM3 1 2 3 4 5 6 Where M1,M2, M3 hve no similarity except they have a max string length of 7. Examples are mcw0045, adl0003, lei0101. Now, what I want to do is Function(M1, M2, M3, datafile) { xnew <- readtable(datafile) name1 <- paste("time",M1",sep"") name2 <- paste(status",M1,sep"") name3 <- paste("x",M1,sep"") fit1 <- survfit(Surv(name1,name2)~name3,data=xnew) . . repeat for M2 and M3...

Hi all, I've been running Xnews through Wine for the past 2-3 years but I find myself unable to run it correctly under any version of Wine past 20031112, everything past it makes it unreliable, or simply dosn't work at all. Main issues lie with windows management & input processing. Any1 having same problem or know how...

...le question ... I'm a new user. I can't understand why R flips the sign of all data values when reading in external text files (tab delimited or csv) with the read.delim or read.csv functions. The signs of data values also seem to be flipped after assigning a new data.frame from within R (xnew <-- edit(data.frame()). What am I doing wrong? Any help would be greatly appreciated. Thanks in advance. -- Nate ----------------------------- Nathan Dieckmann Department of Psychology University of Oregon Eugene, OR 97403 (541) 346-4963 ndieckma at darkwing.uoregon.edu

Dear all, I have several character strings with a high number of different levels. unique(x) gives me values in the range of 100-200. This creates problems as I would like to use them as predictors in a coxph model. I therefore would like to convert each of these strings to a new string (x_new). x_new should be equal to x for the top n categories (i.e. the top n levels with the highest

I have a function XOLD() from a nearly verbatim port of legacy FORTRAN in a package. I have remplemented this function as XNEW() using much cleaner native R and built-in functions of R. I have switched the package to the XNEW(), but for historical reasons would like to retain the XOLD() somewhere in the package directory structure. An assertion through a README or other will point to this historical function and...

I am using Wine 0.9.15 to run a newsreader called Xnews. I have found several sites with Wine configurations for Xnews, but all of the sites I've found refer to modifying the "$HOME/.wine/config" file. The version of Wine I am using doesn't use a config file - it uses system.reg and user.reg. Can I use the modifications from the...

...s from each of other columns for each level of the factor. That is, in the example, to go from the first matrix below to the second. I know SWEEP will take out means, but I want to do this for each level of the factor. f x 1 2 1 0 2 0 2 4 2 2 f xnew 1 1 1 -1 2 -2 2 2 2 0 Thanks [[alternative HTML version deleted]]

...of R and I'm working right now with the ACE function from the acepack library. I Have a question: Is there a way to predict new responses using ACE? What I mean is doing something similar to the following code that uses PPR (Projection Pursuit Regression): library(MASS) x <- runif(20, 0, 1) xnew <- runif(2000, 0, 1) y <- sin(x) a <- ppr(x, y, 2) ynew <- predict(ppr, xnew) Any help would be much appretiated, Thanks in advance, Luis Pineda

Dear colleagues Please could someone kindly explain the following inconsistencies I've discovered when performing logical calculations in R: 8.8 - 7.8 > 1 > TRUE 8.3 - 7.3 > 1 > TRUE Thank you, Emma Jane [[alternative HTML version deleted]]

Hi, I have a problem when I want to add new points (or a new line) to the graph. Some points (or parts of the line) are not shown on the graph because they lie beyond the scale of the axis. Is there a way to overcome this so all points (or the entire line) are shown on the graph? Here's an example of my problem: colors = c("red", "blue") plot(x=rnorm(100,0,1),

I think that this is an easy one... I have a matrix where each row is an (x,y,z) triplet. Given a potential (xnew,ynew,znew) triplet I want to know if the matrix already contains a row with the new values (the space already has that point). I can do it using a for loop, but I would like to know if there is anyway in which I can do it without the for loop. I do it now like this (this algorithm appears to be...

...columns. Some columns are numeric, some are not. I wish to create a function to calculate the mean and standard deviation of each numeric column, and then ?bind? the column mean and standard deviation to the bottom of the dataframe. e.g. tempmean <- apply(data.frame(x), 2, mean, na.rm = T) xnew <- rbind(x,tempmean) I am running into one small problem what is the best way to have sapply ?skip? the non-numeric data and return NA?s?

Hi, final<-data.frame() ?? for (m1 in 4:10) { ?????? for (n1 in 4:10){? ?????????? for (x1 in 0: m1) { ????????????? for (y1 in 0: n1) { final<- rbind(final,c(m1,n1,x1,y1)) res}}}} ?final1<-within(final,{flag<-ifelse(x1/m1>y1/n1, 1,0)}) ?head(final1) #? m1 n1 x1 y1 flag #1? 4? 4? 0? 0??? 0 #2? 4? 4? 0? 1??? 0 #3? 4? 4? 0? 2??? 0 #4? 4? 4? 0? 3??? 0 #5? 4? 4? 0? 4??? 0 #6? 4? 4?

Hello! I have a column in my data frame that I have to split: I have to distill the numbers from the text. Below is my example and my solution. x<-data.frame(x=c("aaa1_bbb1_ccc3","aaa2_bbb3_ccc2","aaa3_bbb2_ccc1")) x library(stringr) out<-as.data.frame(str_split_fixed(x$x,"aaa",2)) out2<-as.data.frame(str_split_fixed(out$V2,"_bbb",2))

...ith assuming a constant movement during the time interval). The 'time distance' bewteen WP3 and WPnew is (120-73) 47 seconds and the 'time distance' between WPnew and WP4 is (153-120) 33 seconds (whereas total time interval between WP3 and WP4 is 80 seconds). WPnew (with coordinates Xnew,Ynew) should then be located at 80/33*100=41.25% from WP3: Xnew = X3 + (X4-X3)*41.25% and Ynew= Y3 + (Y4-Y3)*41.25% 2) Calculate the average location (average of x3,y3 and x4,y4), at which to create a new waypoint at 2 minutes. 3) A simpler alternative is that the location of the 'closer...