xts

问题 I am trying to build a rolling regression function based on the example here, but in addition to returning the predicted values, I would like to return the some rolling model diagnostics (i.e. coefficients, t-values, and mabye R^2). I would like the results to be returned in discrete objects based on the type of results. The example provided in the link above sucessfully creates thr rolling predictions, but I need some assistance packaging and writing out the rolling model diagnostics: In the

问题 On one machine, plot.xts correctly displays data in two columns: On another, things look very different: The code for both is the same: library(zoo) library(xts) library(xtsExtra) sessionInfo() timezone = "UTC" Sys.setenv(TZ=timezone) sampleData = "Time (UTC),CPU,Runqueue,Blocked,MemoryFree,PageIns,ContextSwitches,Wait,Steal 2014-10-15 16:12:11,20,0,0,12222172,0,2549,0,0 2014-10-15 16:12:12,27,1,0,12220732,0,3619,0,0 2014-10-15 16:12:13,30,0,0,12220212,0,2316,0,0" data = as.xts(read.zoo(text

问题 I am wishing to (arithmetically) average daily data and thus convert my daily time series into a weekly one. Following this thread: How does one compute the mean of weekly data by column using R? , I am using the xts library. # Averages daily time series into weekly time series # where my source is a zoo object source.w <- apply.weekly(source, colMeans) The problem I am having is that it averages the series taking tuesday through next monday data. I am searching for options to average my

问题 I have the following data: xtsdata <- structure(c(0.44696179, 0.395227931, 0.477439822, 0.295309508, 0.712614891, 0.689317114, 0.599395023, 0.610971864, 0.337625508, 0.529290134, 0.596002106, 0.412324483, 0.244831259, 0.443123542, 0.484748065, 0.686165972, 0.711764909, 0.604578061, 0.42144923, 0.669898641, 0.735845192, 0.592157589, 0.81714156, 0.380346873, 0.684386001, 0.672967504, 0.508142689, 0.244274776, 0.548213564, 0.417804342, 0.612475603, 0.665148957, 0.756447435, 0.582448567, 1, 1, 1,

问题 I'm trying to convert a daily series into a weekly one ending on Fridays. There are missing values for each series and therefore merge function leave some NAs. I have tried with na.locf and to.weekly but didn't work for me. I'm creating a weekly date object containg all fridays in that period and, because some weeks end on wednesdays or thursdays for some series, I can't match those indexes. Ideally I would like to overwrite the date of the last value in those weeks not ending on fridays.

问题 I really need your help on the following issue: I have two data frames - one containing a portfolio of securities with ISIN and Cluster information. > dfInput TICKER CLUSTER SECURITY.NAME 1 LU0937588209 High Yield Prime Capital Access SA SICAV- 2 LU0694362343 High Yield ECM CREDIT FUND SICAV - ECM Hi 3 IE0030390896 High Yield Putnam World Trust - Global Hi 4 LU0575374342 EM Debt Ashmore SICAV - Emerging Marke 5 LU0493865678 EM Debt Ashmore SICAV - Emerging Marke 6 LU0972237696 EM Debt

问题 I'm trying to collect mutual fund performance data via open and close prices from quantmod. I have scraped a list of 5000 some funds and am trying to loop through and get one open and close price for each fund. I'm having difficulty calling the xts object yielded by getSymbols() as it is called invisibly into the environment. Since the object is stored as its ticker name, I tried calling it by its ticker name. Code so far: ## loop thru list and use quantmod to calculate performance from 1/2

问题 I am using xtsExtra to plot some scatter graphs of xts objects and wanted to draw a horizontal line through zero but it looks like its in the wrong place...please see the code below? is this a bug? set.seed(123) require(xts) f <- xts(rnorm(100,0.0001,0.003),Sys.Date()-c(100:1)) f1 <- xts(rnorm(100,0.0001,0.003),Sys.Date()-c(100:1)) require(xtsExtra) plot(f,f1) abline(h=0,col='red') 回答1: Jeff Ryan may have answered this here: Try, abline(v=.index(X)[50], col="red") Note the "dot" in .index .

问题 I am trying to solve this issue for past 3 months. Please help. I have tick data (Price and Volume) for many stocks belonging to a single exchange. Each stock has its own .rds file on the hard disk. I am interested in cleaning it up: merge multiple same time stamps by taking median subset data for exchange hours only aggregate it over 20 minutes by previous tick aggregation I know that the function aggregatets in highfrequency package can perform the previous tick aggregation operation.

问题 I'm using the zoo and xts package for analysing financial data. ts package is not very suitable since financial series have weekend with no data available. I read about the apply function availbale in the xts package apply.daily(x, FUN, ...) apply.weekly(x, FUN, ...) apply.monthly(x, FUN, ...) apply.quarterly(x, FUN, ...) apply.yearly(x, FUN, ...) this apply function over calendar periods and thought that something like that will work in order to get the end of week value but it seems not to