similar to: Need help to optimize a piece of code involving zoo objects

(Sorry, sent the message before I finished it) Hello, everyone I have a long script that uses zoo objects. In this script I used simple moving averages and these I can very efficiently calculate with filter() functions. Now, I have to use special "exponential" moving averages, and the only way I could write the code was with a for-loop, which makes everything extremely slow. I don't

Dear R-helpers, It seems to me that a character zoo cannot be coerced to a numeric zoo. Below is a minimal example. Can someone tell me what I have done wrong? > z<-zoo(1:4,order.by=1:4) > coredata(z)<-as.character(coredata(z)) > str(z) ‘zoo’ series from 1 to 4 Data: chr [1:4] "1" "2" "3" "4" Index: int [1:4] 1 2 3 4 >

My problem is the following : I create 2 zoo objects and then I try to subset one of them using logic. indicesthatpass is a vector of trues and falses but when I send it into bckret, it returns an empty bckret. Obviously it has something to do with bckret being a zoo object and if I do the same subsctripting off of coredata(bckret), I'm confident it will work. But, I need to keep the minute

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

Hi, Just wondering for the SMA and EMA in package TTR, is it possible to me to code it so that, say if I need to calculate SMA (x, n=100), when the sample size is less than 100, it will give me the SMA (x, k) where k is the sample size of the data? Right now it only gives me an invalid n error. Thanks! [[alternative HTML version deleted]]

Dear list-reader, by running the following script: library(zoo) sessionInfo() search() packageDescription("zoo") data(EuStockMarkets) dax <- as.zoo(EuStockMarkets[1:10, "DAX"]) daxr <- diff(log(dax)) identical(as.vector(qnorm(daxr)), qnorm(coredata(daxr))) qqnorm(coredata(daxr)) qqnorm(daxr) qqnorm() produces an error: > qqnorm(daxr) Fehler in if (xi == xj) 0L

Hi, I'm having trouble with quantmod's addTA plotting functions. They seem to work fine when run from the command line. But when run inside a function, only the last one run is visible. Here's an example. test.addTA <- function(from = "2010-06-01") { getSymbols("^GSPC", from = from) GSPC.close <- GSPC[,"GSPC.Close"] GSPC.EMA.3

Hello, I'm trying to use na.spline (package zoo) to fill some missing data in a time series. this works fine, however, if I apply the 'maxgap' argument, I always get the error: <------ Error in na.spline.vec(x., coredata(object.), xout = xout., ...) : attempt to apply non-function ------> I couldn't find a similar error for this case in the mailing lists and zoo vignette,

R Friends, I have data from which I would like to learn a more general (smoothened) trend by applying data smoothing methods. Data points follow a positive stepwise function. | x x | xxxxxxxx xxxxxxxx | x x |xxxx xxx xxxx | xxxxxxxxxxxxxxxxx | |

Hi Would anyone have any pointers on how to slice up a large zoo table. I have the following structure: - > str(ZOO_OBJ) ?zoo [1:632, 1:83] 30.4 30.4 30.4 30.4 30.3 ... ?- attr(*, "dimnames")=List of 2 ??..$ : NULL ??..$ : chr [1:83] "COL1" "COL2" "COL3" "COL4" ... ?- attr(*, "index")= POSIXct[1:632], format: "2009-05-01

Full_Name: John P Cavanaugh Version: .99 OS: linux Submission from: (NULL) (24.116.10.99) dataset$ema12 <- EMA (dataset$Close,12) dataset$ema26 <- EMA (dataset$Close,26) dataset$MACD_fast <- dataset$ema26 - dataset$ema12 dataset$MACD_slow <- EMA(dataset$MACD_fast,9) dataset$MACD_hist <- dataset$MACD_fast - dataset$MACD_slow # This line doesnt work!!! But... if I does work if I

Hi there I have some timeseries data which I plot in a OHLC Plot. In the same plot I'd like to have the EMA of this timeseries. I tried to add the EMA point to OHLC with lines(), but this doesn't work. Has anyone an idea how to handle it? Regards, Michael Zak

Can somebody help me in finding package/Example in R which could do EMA(Exponential Mean Average). I installed "TTR" package but the 'EMA" function which I was trying to use is giving the following error. Error: Could not find function "EMA" Thanks & Regards, Thomas [[alternative HTML version deleted]]

  Hi,   The code below does exactly what I want in sequential mode. But, it is slow and I want to run it in parallel mode. I examined some windows version packages (parallel, snow, snowfall,..) but could not solve my specific problem. As far as I understood, either I have to write a new function like sfRollapplyr or I have to change my code in a way that it utilizes lapply, or sapply instead of

Dear Rui, Not working. I have entirely removed the column containing % but am still bootless: > head(coredata(INFYTX)) INFY Historical Data INFY Historical Data INFY Historical Data INFY Historical Data [1,] "47.26" "44.28" "47.56" "44.28" [2,] "46.30" "44.92"

Dear members, I have an xts object: > head(INFYTX) INFY Historical Data INFY Historical Data.1 INFY Historical Data.2 2003-04-16 "47.26" "44.28" "47.56" 2003-04-17 "46.30" "44.92" "46.53" 2003-04-21 "45.82"

?s 19:57 de 12/04/2023, akshay kulkarni escreveu: > Dear members, > I have an xts object: > >> head(INFYTX) > INFY Historical Data INFY Historical Data.1 INFY Historical Data.2 > 2003-04-16 "47.26" "44.28" "47.56" > 2003-04-17 "46.30" "44.92"

Isn't this like trying to tie up the horse after it has left the barn? Why not figure all this out _before_ converting to xts? On April 12, 2023 12:29:49 PM PDT, akshay kulkarni <akshay_e4 at hotmail.com> wrote: >Dear Rui, > Not working. I have entirely removed the column containing % but am still bootless: > >> head(coredata(INFYTX)) > INFY

Thanks, Writing plot(addTA()) worked fine. I find myself with such mixed feelings about R. After finding that addTA worked fine at the command line but not in a function, I puzzled for a long time about what kind of virtual machine structure could possibly account for that. I couldn't think of any. It turns out that this isn't due to an R virtual machine structure. The reason addTA adds

Dear all, To explain my problem I am attaching a demonstration package "myclasspkg": I have the following two S4 classes with similar inheritance: SubSubClassA <- SubClassB <- BaseClass SubSubClassB <- SubClassB <- BaseClass In R I am calling the following functions: > library(myclasspkg) > subA <-