similar to: Preserving both yearmon and numeric data in an xls object

R-listers, I am using xts with a yearmon index, but am getting some inconsistent results with the date index when i drop observations (for example by using na.omit). The issue is illustrated in the example below. If I start with a monthly zooreg series starting in 2009, yearmon converts this to "Dec-2008". Not such a worry for my example, but strange. Having converted to xts, i drop

oky.. thank you very much to all of you On Sat, Sep 16, 2017 at 2:06 PM, Eric Berger <ericjberger at gmail.com> wrote: > You can just use the same code that I provided before but now use your > dataset. Like this > > df <- read.csv(file="data2.csv",header=TRUE) > dates <- as.Date(paste(df$year,"-01-01",sep="")) > myXts <-

You can just use the same code that I provided before but now use your dataset. Like this df <- read.csv(file="data2.csv",header=TRUE) dates <- as.Date(paste(df$year,"-01-01",sep="")) myXts <- xts(df,order.by=dates) head(myXts) #The last command "head(myXts)" shows you the first few rows of the xts object year cnsm incm wlth

Assuming the input data.frame, DF, is of the form shown reproducibly in the Note below, to convert the series to zoo or ts: library(zoo) # convert to zoo z <- read.zoo(DF) # convert to ts as.ts(z) # Note: DF <- structure(list(year = c(1980, 1981, 1982, 1983, 1984), cnsm = c(174, 175, 175, 172, 173), incm = c(53.4, 53.7, 53.5, 53.2, 53.3), with = c(60.3, 60.5, 60.2, 60.1, 60.7)),

Hello, I noticed something odd when working with data frames and xts objects. If I read in a CSV file, R creates a nice data.frame. This works well. If I then convert to an XTS object, I see that all the values in the data are now quoted. My data is a mix of numeric and character. This is usually seen when converting a data.frame to a matrix, as R will treat all the data as the same class.

thankx to everyone for your valuable suggestions. one query regarding the GARCH model. I have applied the GARCH model for the same data that I send you all . and my results coming like Error in .sgarchfit(spec = spec, data = data, out.sample = out.sample, : ugarchfit-->error: function requires at least 100 data points to run can you suggest something on it. On Fri, Sep 22, 2017 at 6:02

Folks, I have some weekly dataseries that I convert to monthly xts (with yearmon indices), and obtain the two following extracts: > str(sig) An 'xts' object from Apr 1998 to Sep 1998 containing: Data: num [1:6, 1] 0.0083 0.2799 -0.2524 -0.0119 0.18 ... - attr(*, "dimnames")=List of 2 ..$ : NULL ..$ : chr "e1" Indexed by objects of class: [yearmon] TZ:

Hullo I may have missed something blindingly obvious here. I'm using xts to handle some timeseries data. I've got daily measurements for 100 years. If I try to reduce the error rate by taking means of each month, I'm getting what at first sight appears to be conflicting information. Here's a small subset to show the problem: A small set of data: > vv x

Hi R programmers, I have stumbled across what seems a very simple problem. My goal is to create a xts time series object which contains vectors as values. In other words, I try to create something like this: 2009-01-01 => c('aa', 'bb', 'dd') ... 2010-02-01 => c('mm') I have figured out parts of separately. Here's what works (new xts time-series with

Looking for a little help figuring out what's driving gaps in data after merging two xts objects (msci.m and x2). The merge statement I'm using is ... y <-merge(x2,msci.m, all=FALSE). Here's info on the output , y: head(y) t-bill msci Sep 1985 7.310 316.963 Mar 1986 6.560 463.471 Jun 1986 6.180 498.791 Jul 1987 6.200 778.898 Aug 1987 6.400 833.519 Nov 1987

Good afternoon, I have been experiencing a lot of crashes working with large vectors in R. Specifically, I am using XTS of length of minimum 120k elements. My problem is that I cannot display the vector (otherwise R crashes), I cannot plot it either (otherwise R crashes). That could be solved by reducing the amount of points. However, I have been performing some statistical opreations on is

Hi, I'd like to make a time series at an annual frequency. > a<-xts(x=c(2,4,5), order.by=c("1991","1992","1993")) Error in xts(x = c(2, 4, 5), order.by = c("1991", "1992", "1993")) : order.by requires an appropriate time-based object > a<-xts(x=c(2,4,5), order.by=1991:1993) Error in xts(x = c(2, 4, 5), order.by =

I'm using R 2.10.0, with zoo 1.5-8. The release notes for zoo 1.5-8 claim a bug with unique for yearmon objects has been fixed, but I'm still having problems. Browse[1]> tmp2 [1] "Dec 1996" "Dec 1996" Browse[1]> unique(tmp2) [1] "Dec 1996" "Dec 1996" Browse[1]> unique(unique(tmp2)) [1] "Dec 1996" Browse[1]> as.numeric(tmp2) -

It looks like a timezone issue, and it's causing confusion to me at least. My original data: gmt <- c("19880101 0000", "19880101 0100", "19880101 0300", "19880101 0400", "19880101 0500", "19880101 0600") These were converted to local dates/times with akst<-strptime(gmt,format="%Y%m%d %H%M")-(3600*9) # because I want

Hello, In zoo package, if I would like the time frame to be 1981M01 to 1982M12, then I code time_0<-as.yearmon("1981-01")+(0:23)/12 However, if the time frame of interest becomes 1981M01 to 2011M12, it is relatively hard to calculate the number of months. Is there any faster way to do it? Thanks, miao [[alternative HTML version deleted]]

I have following dataset: > res [,1] [,2] [,3] [1,] 1946 4 1.27 [2,] 1946 5 1.27 [3,] 1946 6 1.27 [4,] 1946 7 1.27 [5,] 1946 8 1.52 [6,] 1946 9 1.52 [7,] 1946 10 1.52 [8,] 1946 11 1.52 [9,] 1946 12 1.62 [10,] 1947 1 1.62 [11,] 1947 2 1.62 [12,] 1947 3 1.62 [13,] 1947 4 1.87 [14,] 1947 5 1.87 [15,] 1947 6 1.87 Now I write following code

> On 15 Sep 2017, at 11:38, yadav neog <yadavneog at gmail.com> wrote: > > hello to all. I am working on macroeconomic data series of India, which in > a yearly basis. I am unable to convert my data frame into time series. > kindly help me. > also using zoo and xts packages. but they take only monthly observations. > > 'data.frame': 30 obs. of 4 variables:

I really can't figure out how to get and set array indices from the c interface. so to get an element I'm calling tindex = *fn\SymbolTable(*index\name) index = LLVMBuildLoad(builder,tindex,"index") arr = *fn\SymbolTable(*array\name) arrptr = LLVMBuildLoad(Builder,arr,"arrayptr") tmp = LLVMBuildGEP(Builder,arrptr,index,0,"ptr") ptr =

To the R development team; I found an unusual behavior in zoo when I upgraded to R 2.11.0 - it abruptly terminated when I performed certain operations on large zoo objects. I sent an e-mail to Achim Zeileis and he said this was a potential bug that I should report to the R development team. The details are given below in the thread below. Basically, I can crash R with this code: library(zoo)

hello to all. I am working on macroeconomic data series of India, which in a yearly basis. I am unable to convert my data frame into time series. kindly help me. also using zoo and xts packages. but they take only monthly observations. 'data.frame': 30 obs. of 4 variables: $ year: int 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 ... $ cnsm: num 174 175 175 172 173 ... $ incm: