similar to: Extending time series

I tried to assign values to specific elements of a time series and got in trouble. The code below should be almost self-explanatory. I wanted to assign 0 to the first element of x, but instead I assigned zero to the second element of x, which is not what I wanted. Is there a function that will allow me to do this without going into index arithmetic (which would be prone to errors)? FS >

One thing that has given me trouble is the fact that the time series implementation in the class ts relies on the concept of a "start" to the time series. For example, if I have ts1 <- ts(c(1,2,3)) dts1 <- diff(ts1) then dts1 will be a vector c(1,1) but with the attribute start = 2. Similarly, when one takes lags the "start" is moved around and the underlying vector

Can someone shed some light on this obscure portion of the help for lm? "Considerable care is needed when using 'lm' with time series. Unless 'na.action = NULL', the time series attributes are stripped from the variables before the regression is done. (This is necessary as omitting 'NA's would invalidate the time series attributes, and if

I declared the environment of the function myfun to be NULL as follows: environment(myfun) <- NULL Later on I called that myfun and got an error message because the function index() in the zoo package was called inside myfun and was not visible: Error in myfun(args) : couldn't find function "index" I tried to use zoo::index() instead of index(), but that did not work. In fact,

I am trying to find a way to assign values to elements of a vector that will be defined by a user. So I don't have the name of the vector and cannot hard code the assignment in advance. In the example below I have to get() the vector using its name. When I try to assign to an element I get an error: > a <- c(1,2,3) > get('a')[1] <- 0 Error: Target of assignment expands to

This is probably a dumb question, but I cannot figure it out. Why does this happen? dt <- as.Date("1954-02-01") > as.character(dt) [1] "1954-02-01" > sapply(c(dt), as.character) [1] "-5813" Thanks. FS

I wanted to create a list with the names of variables and their values. So I wrote the following function. add.to.list.names.vars.1 <- function(lnv, vnv) { i <- 1 while (i < length(vnv)) { z <- as.character(eval(substitute(quote(vnv[i+1])))[[2]][[i + 2]]) lnv[[vnv[i]]] <- list(Name = z, Value = vnv[i+1]) i <- i + 2 } lnv } It works, but it is very

I discovered a bug in a program I am writing which was due to the program using a global variable within a function. For example, myfunc <- function(x) { y} That is, I made a mistake when defining the function and wrote "y" when I should have written "x". However, there was a variable y in the global environment and the function "worked" but gave the wrong

Hello! Recently I got report that my package mar1s doesn't pass checks any more on R 3.0.2. I started to investigate and found the following difference in multivariate time series handling in R 3.0.2 compared to R 2 (I've checked on 2.14.0). Suppose I wish to calculate seasonal component for time series. In case of multivariate time series, I wish to process each column independently.

I thought system.time() would return three numbers, the first two adding up to the third one. However, this does not hold in my system running Windows Vista Home Premium, with an Intel Core 2 Duo processor. For example, using the code in the help for system.time() (with one zero added), I got: > system.time(for(i in 1:100) mad(runif(10000))) user system elapsed 0.27 0.00 0.25 Is

Dear all, Before I file this as a bug, I wanted to check if I didn't miss something. The help page of lag() says that the function returns a time series object. It actually does return something that looks like a ts object (the attribute tsp is set). But when using a vector, the class "ts" is not added to the result: > avec <- 1:10 > lag(avec) [1] 1 2 3 4 5 6 7 8

Dear Helpers, I am looking for methods and tools to compare and then to concatenate two successive time series. They are both in the same frequency and they describe one phenomena. There is no time gap between them. The problem is that the method of measurements has changed between both time series and they are no statistically the same. I would like to merge them to receive one homogeneous

I tried toy problems and there doesn't seem to be a basic problem between lm() and ts objects: X = data.frame(x=c(1,2,7,9), y=c(7,2,3,1)) lm(y ~ x, X) X <- lapply(X, function(x) ts(x, frequency=12, start=c(1994,7))) lm(y ~ x, X) and this works fine - whether you do an lm() before or after making ts objects, it's okay. But I have a situation where things aren't okay.

Hi all. Currently, if you try: > lag.plot(1:10) you get superposed labels '1' and '10'. Things go worse in more extreme cases: x <- ts(1:10) x1 <- lag(x, 4) plot(x1, x) This is due to a mistake in plot.ts. My suggestion is the following really minimal patch to plot.ts: @@ -530,7 +530,7 @@ plot.ts <- text(xy, labels =

Marcus Eger <marcus.eger@physik.uni-marburg.de> writes: > > time(sqrt(arrts)) > Time Series: > Start = c(1, 1) > End = c(5, 1) > Frequency = 1 > [1] 1 2 3 4 5 Looks like a bug... > ---------------------------------------------------------------------------- > 2. (At least) boolean indexing with matrices does not seem to work > properly: >

This one showed up while looking at one of Ripley's other reports: > data(freeny) > model.frame(y~1,data=freeny,subset=1:10) y 1962.25 8.79236 1962.5 8.79137 1962.75 8.81486 1963 8.81301 1963.25 8.90751 1963.5 8.93673 1963.75 8.96161 1964 8.96044 1964.25 9.00868 1964.5 9.03049 > model.frame(y~1,data=freeny,subset=1:10)$y Warning: Replacement length not a

Suppose I have multiple time series with names for each one, for example, x <- ts(matrix(rnorm(30,0,1),10,3), names=c("Juan", "Tuey", "Trey"), frequency=4) So now, as I start to explore these series, if I do everything at once, the names stay attached to the series. For example, plot(x) # gives a plot of the series with their names acf(x) # gives the ACFs &

Hello, I am wondering how I should set up the tsp attribute (available through attr(x, "tsp")) of a dataset x? Let's assume that x has 100 points, and I want to set the frequency to 4. I tried: > attr(x,"tsp")<-c(1,100,4) Error in attr(x, "tsp") <- c(1, 100, 4) : invalid time series parameters specified Is there any other way to set the frequency of

Hello, I have a question on how to tabulate the time series data. I use RStudio, but if can be done in any other R editor, it should work in RStudio as well. > a1<-11:22 > a1ts<-ts(a1, frequency=4, start=c(1978,1)) > a1ts Qtr1 Qtr2 Qtr3 Qtr4 1978 11 12 13 14 1979 15 16 17 18 1980 19 20 21 22 If I click the variable "a1ts" on the

Hi! I had a database with some variables in sequence. Let me say: TX01, TX02, TX03 and TX04. But I need to run some regressions changing the variables... so: variable <- paste("TX0", 1:4, sep="") for(i in 1:4){ test[i] <- lm(variable[i] ~ INCOME, data=database) } But doesn't work... lm tries to find a variable inside database named variable[i] ... Suggestions?