similar to: R - Confidence Intervals

Hello all, Just joined this mailing list -- not sure if this is the right list to send this question, but I have a question about cross-compiling R. I am working with R-1.9.1.tgz. It may just be with my version of mingw32, but it seems that expm1 is not defined, so I tried to ensure that HAVE_EXPM1 was #undef'ed before cross-compiling. The problem is that, in <include/Rmath.h> if

Hi, the snippet of code below works, but I would like to know how to feed the function merge.zoo the contents of CADstocknames rather than having to hard code it into the merge.zoo command. I think I must be missing something simple, but I cannot for the life of me figure it out. Thanks in advance for any enlightenment offered. library(zoo) CADstocknames <-

Dear all, I have an error message, when I try to convert a zoo object (called test) to ts (on R 2.4.0, Package zoo version 1.2-1, Windows XP) > test 1994-05-10 1994-06-09 1994-07-09 0.0024943889 0.0024881824 0.0006955831 > str(test) atomic [1:3] 0.002494 0.002488 0.000696 - attr(*, "index")=Class 'Date' num [1:3] 8895 8925 8955 > is.regular(test) [1] TRUE

Folks, I often build up R objects starting from NULL and then repeatedly using rbind() or cbind(). This yields code like: a <- NULL for () { onerow <- craft one more row a <- rbind(a, onerow) } This works because rbind() and cbind() are forgiving when presented with a NULL arg: they act like nothing happened, and you get all.equal(x,rbind(NULL,x)) or all.equal(x,cbind(NULL,x)).

i have time series of momentum signal. I want to get the date of each of the "-1" signal period. for example , the first period of -1 signal begins on 2005-9-21 and ends on 2005-9-28. 2nd period of -1 signal begins on 2005-09-30 and ends on 2005-10-28. Thx Cameron date Px 200MA Signals 2005-09-15 26.27 25.83865 1 2005-09-16 26.07 25.83275 1

I want to set up a model with a formula and then run dynlm(formula) because I ultimately want to loop over a set of formulas (see end of post) R> form <- gas~price R> dynlm(form) Time series regression with "ts" data: Start = 1959(1), End = 1990(4) <snip> Works OK without a Lag term R> dynlm(gas ~ L(gas,1)) Time series regression with "ts" data: Start =

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]]

Hello This is my first post on this forum and I hope someone can help me out. I have a datafile (weeklyR) with returns of +- 100 companies. I acquired this computing the following code: library("tseries"); tickers = c("GSPC" , "BP" , "TOT" , "ENI.MI" , "VOW.BE" , "CS.PA" , "DAI.DE" , "ALV.DE" ,

Dear R users, I am trying to carry out MLE of the time-varying CAPM using the FKF package. My approach so far has been to try and adapt the example given in the help file found using ?fkf which demonstrates the MLE of an ARMA(2,1) model. When I attempt to run my R code (given below) I get the following error: Error in fkf(a0 = sp$a0, P0 = sp$P0, dt = sp$dt, ct = sp$ct, Tt = sp$Tt, : Some of

Ryacas is now available on CRAN. (Previously it was available on the Omegahat repository.) Ryacas is an R package that provides an interface from R to the yacas computer algebra system. It can be used for computer algebra, exact arithmetic, ASCII pretty printing and R to TeX output. R, yacas and Ryacas are all free software packages distributed under the GPL version 2. Ryacas is written in R.

Ryacas is now available on CRAN. (Previously it was available on the Omegahat repository.) Ryacas is an R package that provides an interface from R to the yacas computer algebra system. It can be used for computer algebra, exact arithmetic, ASCII pretty printing and R to TeX output. R, yacas and Ryacas are all free software packages distributed under the GPL version 2. Ryacas is written in R.

Dear R People: I have the following code that I use to convert a monthly zoo object to a data.frame, and it works perfectly: library(tseries) z <- get.hist.quote(instrument=inst1, start=start1,end=end1, quote=quot1,comp = "m") y <- as.ts(aggregate(z, as.yearmon, tail, 1)) y.df <- data.frame(y=y,time=time(y)) y.df$x <- ts(y.df[,1]) tsp(y.df$x) <-

list(...), I am working with environmental time series (eg rainfall, stream flow) that have attached quality codes for each data point. The quality codes have just a few factor levels, like "good", "suspect", "poor", "imputed". I use the quality codes in plots and summaries. They are carried through when a time series is aggregated to a longer time-step,

Hi, I let xzoo be an empty object: > xzoo<-{} and I have an existing zoo object x1zoo_f. I would like to combine the two to make a new zoo object, and continue doing so in a loop, which is not shown here. However, when I type > xzoo<-cbind(xzoo, x1zoo_f) An error message emerges Error in zoo(structure(x, dim = dim(x)), index(x), ...) : “x” : attempt to define

Dear All, There is an example for the priceIts function (the its package) which does not work for me as expected. > ?priceIts > x1 <- priceIts(instrument = c("^ftse"), start = "1998-01-01", + quote = "Close") Error in validObject(.Object) : invalid class "its" object: Missing values in dates > x2 <-

 Hello! > I have a very simple set of data and I would like to analyze > them with probit analysis. > The data are: X    Event    Trial > 1210  8        8 > 121  6        8 > 60.5  6        8 > I want to estimate the value of X that will give a 95% hit > rate (Event/Trial) and the corresponding 95% CI. > you can help me? Thanks!! > Trinh  [[alternative HTML version

Hello, I am fitting data using different methods e.g. Local Polynomial and Smoothing splines. The data is generated out of a true function model with added normally distributed noise. I would like to know "how often the confidence band for all points simultaneously contain all true values". I can answer the question for one point in the following way: e.g. #

This is a function I coded a few years ago to calculate a confidence interval for a coefficient of variation. The code is based on a paper by Mark Vangel in The American Statistician. I have not used the function much, but it could be useful for comparing cv's from different groups. Kevin Wright confint.cv <- function(x,alpha=.05, method="modmckay"){ # Calculate the

hi, at first; thanks for the help on getting confidence intervals in R. now I have a pure statistical question. I hope you don't mind if I ask ... I have an expectation of how large my beta-weight in a regression should be - so I have an "ideal" or expected regression line. Now the real beta-weight is less then the expected and when I draw the confidence interval lines

Hi, I know this is not exactly an R question but may be someone will nice enough to give me a pointer. I'm using nnet to fit a non linear univariate function. I wonder if there is a way to estimate a confidence interval for the predicted output beside using the residuals? The data set I use is relatively small and I use only a few (5:10) of these as test set or should I say validation set.