similar to: aggregate.ts (PR#376)

aggregate.ts does not behave in the same way as the equivalent method aggregate.rts in S-PLUS. In particular it - changes the start of the time series - tends to have a length which is 1 shorter For example: R> x <- ts(1:10) R> aggregate(x, nfreq=0.5, FUN=min) Time Series: Start = 2 End = 8 Frequency = 0.5 [1] 2 4 6 8 S> x <- rts(1:10) S> aggregate(x, nf=0.5, fun = min) [1]

Consider the following scrap of code: > x<- ts(1:50,start=c(1,11),freq=12) > y <- aggregate(x,nfreq=4) > c(y) [1] 6 15 24 33 42 51 60 69 78 87 96 105 114 123 132 141 > y Error in rep.int("", start.pad) : invalid number of copies in rep.int() > tsp(y) [1] 1.833333 5.583333 4.000000 So we can aggregate into quarters, but we cannot print it using

Consider the following scrap of code: > x<- ts(1:50,start=c(1,11),freq=12) > y <- aggregate(x,nfreq=4) > c(y) [1] 6 15 24 33 42 51 60 69 78 87 96 105 114 123 132 141 > y Error in rep.int("", start.pad) : invalid number of copies in rep.int() > tsp(y) [1] 1.833333 5.583333 4.000000 So we can aggregate into quarters, but we cannot print it using

Hi, I have a ts object with a frequency of 4, i.e., quarterly data, and I would like to calculate the mean for each quarter. So for example: > ts.data=ts(1:20,start=c(1984,2),frequency=4) > ts.data Qtr1 Qtr2 Qtr3 Qtr4 1984 1 2 3 1985 4 5 6 7 1986 8 9 10 11 1987 12 13 14 15 1988 16 17 18 19 1989 20 If I do this manually, the mean

I'm probably apporaching this all wrong to start but.... Suppose I have a monthly time series and I want to compute the mean of months 6,7, and 8. I want to plot the original time series and the seasonal time series, one above the other. When I do that as below the time series don't line up for reasons that are obvious. How can I change the base of the seasonal time series so I can make

Hello R users, I'm a newby to R (and programming software at large) and I would need some help to sum up event data at discreet time and irregular time interval into a hourly frequency. Here is an example of my time series frame (irregular time-serie object - irts in the tseries package): time value 2008-12-19 19:11:03 GMT 1 2008-12-19 19:12:00 GMT 0 2008-12-19

I have a monthly price index series x, the related return series y = diff(log(x)) and a POSIXlt date-time variable dp. I would like to apply annual blocks to compute for example annual block maxima and mean of y. When studying the POSIX classes, in the first stage of the learning curve, I computed the maximum drawdown of x: > mdd <- maxdrawdown(x) > max.dd <- mdd$maxdrawdown > from

Dear list, I have a problem with freq from prettyR. Please have a look at my syntax with a litte example: library(prettyR) #Version 1 test.df<-data.frame(q1=sample(1:4,8,TRUE), gender=sample(c("f","m"),8,TRUE)) test.df freq(test.df) #No error message #Version 2 test.df<-data.frame(gender=sample(c("f","m"),8,TRUE), q1=sample(1:4,8,TRUE)) test.df

I have a time series vector (not necessarily ts class) that has NAs in it. How can I omit the NAs when using aggregate.ts() to compute a function on each window? If there is at least one non-NA value in each window, I'd like to proceed with evaluating the function; otherwise, I would like NA returned. I'm not wedded to aggregate.ts and don't need ts class if there is another fast,

I've stumbled across an issue with aggregate.ts that either is due to a misuse of %/% or something deeper relating to numerical precision on Windows. The test code is x <- rep(6:10, 1:5) as.vector(aggregate(as.ts(x), FUN = mean, ndeltat = 5)) On Linux and Mac I get the correct answer > x <- rep(6:10, 1:5) > as.vector(aggregate(as.ts(x), FUN = mean, ndeltat = 5) [1] 7.2 8.8

Hello, I'm attempting to plot out a series of bar charts of recency, frequency and monetary (RFM) scores using recency as a conditioning variable so we can see the details of the FM components. My dataset looks like this: rfmCellPop{rfm_score, orecency, ofrequency, omonetary, cellpop} Where rfm_score is the composite score (cellID), oRecency, oFrequency and oMonetary are the respective

Hi, I am getting unexpected behaviour from aggregate.ts(). The 'ndeltat' argument is effectively being reduced by 1 in some cases, even when it is an integer, with the result that the blocks to be aggregated are not of the expected size, and also that the end() of the aggregated series is much later than the end() of the original series. rawts <- ts(rep(1:10, each = 5), start = 1) ##

Dear R-help, I have fitted a glm logistic function to dichotomous forced choices responses varying according to time interval between two stimulus. x values are time separation in miliseconds, and the y values are proportion responses for one of the stimulus. Now I am trying to extrapolate x values for the y value (proportion) at .25, .5, and .75. I have tried several predict parameters, and they

Hola: Ante todo, gracias por las respuestas. El 03/06/13 01:23, Oscar Perpiñán Lamigueiro escribió: > > Hola, > > Si no te entiendo mal, necesitas la conversión a matriz como paso > intermedio para agregar por meses (o cualquier unidad temporal). ¡Hum! No estoy seguro de que agregar sea lo que quiero hacer. > Si es > así, te aconsejo que uses el paquete zoo y el método

This relates to a message from Christophe Pallier to r-help some time ago. Like myself, he finds aggregate very useful, but the interface a little cumbersome. I've implemented a more compact formula interface, found at the bottom of this message: data(ToothGrowth) # I used to aggregate like this: aggregate(list(len=ToothGrowth$len),

The documentation for `aggregate` makes it sound like aggregate.formula should behave identically to aggregate.data.frame (apart from the way the parameters are passed). But it looks like aggregate.formula is quietly removing rows where any of the "output" variables (those on the LHS of the formula) are NA. This differs from how aggregate.data.frame works. Is this expected behavior?

Dear all, I want to aggregate() my data based of the classes of a factors, just as in the help file, but how do I define the "Region varable" in the ?aggregate example? Now, the column is just like any other in my data matrix. As I understand it from ?(state), state contains a matrix with the columns Pop, Income etc., but Region is somehow separated. I noted below that as.list() is

Hi, I'm having some problems with the aggregate() function in the {stats} package, and the documentation doesn't address them. 1) Why would the first line work, but the second not? According to the help file, it accepts a "data=" argument. > with(tsrc, aggregate(x=DistRatio, by=list(Condition), FUN=mean)) Group.1 x 1 Congruent 1.741789 2 Mismatch 1.771425

Dear all, I try to summarise my data per category using aggregate, but for some reason I get the error message "sum" not meaningful for factors even though my vector is numeric. The data set is shown below. Could someone please give a hint. Thanks in advance! Sincerely, Tord > names(test) [1] "ObjektID" "tallstubbyta" > is.factor(test$ObjektID);

This question is about column names returned by the aggregate function. Consider the following example df <- data.frame( id = c(rep('11',30),rep('22',30),rep('33',30)), value = c(rnorm(30,2,0.5), rnorm(30,3,0.5), rnorm(30,6,0.5)) ) aggregate(df[,c("value"),drop=FALSE], by=list(id=df$id), max) output: id value 1 11 2.693528 2 22 3.868400 3 33