similar to: SOLVED plotting time series

Hi List, I have the following time series and i want to be able to plot it while having the x-axis running from 1998 to 2006 but in a bi-annual format So here is my example: x<-sample (10:100, 17) x<-ts(x, start=c(1998,1), frequency=2) plot(x) When I plot the ts it goes from 1998 to 2006 by 2years, when in fact i want it to go from 1998 to 2006 with the following form:1998 may, 1998

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.

Good morning! I have 4 questions which trouble me: 1. I want to test the hypothesis that the 2 proportions (the mean of a binomial) which come from 2 different samples are equal. I want to use the following function z= (p1-p2)/ sqrt((p1(1-p1)/n1)+(p2(1-p2)/n2)) which is one of the standard formulas for this case. Is there such a function in R? p1=the proportion from the first sample n1=the

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

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

>represented. They are now R "objects" similar to S-PLUS "rts" >time series, but they are 3-dimensional arrays (iterations x variables >x chains). This seems like the best choice of data structure to me >but if someone else has thought more deeply about this tell me now >before I rewrite all my code! Martyn A couple of years ago I wrote a kernel of routines

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

Hi guys, I am logging data about my body (weight, body fat, blood pressure, ..) in a .csv file and would like to plot this as a time series. I uploaded the (noisified) .csv, you can see the link in the code I have so far (you can run the code directly as-is): df.raw <- read.csv("http://www.chaotic-neutral.de/temp/stats-noised.csv", sep=";", dec=".")

I have the following timeseries "tab" ===================================== > str(tab) mts [1:23, 1:2] 79.5 89.1 84.9 75.7 72.8 ... - attr(*, "dimnames")=List of 2 ..$ : NULL ..$ : chr [1:2] "Ipex...I" "Omel...E" - attr(*, "tsp")= num [1:3] 2006 2008 12 - attr(*, "class")= chr [1:2] "mts" "ts" > tab

Good morning, I hope someone can help with these questions, or perhaps suggest one of the other R-lists? I have two questions: 1. Why am I getting this warning? 2. Why is the second example "Point Forecast" the same value, I do not see that in previous attempts with similar but different data sets as in example 1? Example1: dat3 <- structure(c(3539122.86, 3081383.87,

I'm playing with predict.Arima in the 3/19/02 development snapshot of R-devel. The following produces an error message because x is not of class "ts": R> x <- rnorm(20) R> obj <- arima(x, c(2,0,0)) R> predict(obj) Error in round(x, digits) : Non-numeric argument to mathematical function Granted the documentation for arima says x should be a time-series, but

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.

I have a suggestion for kernapply for ts objects. When we choose the option circular=F, the returned series don't have the correct dates. The removed dates are all at the beginning instead of half at the beginning and half at the end. It is particularly useful when we need to smooth the series (or remove a trend using a filter) before estimating a model (like in macroeconomics) or simply

Good afternoon! I'm trying to model a ts but unfortunately i'.m very new to this kind of modeling so i 'll be very grateful if you have an advice. This was my syntax:

Dear list, I have to look examine hourly time - series and would like to plot variable section of them using plot.zoo. Hourly time series data which looks like this: YYYY MM DD HH P-uk P-kor P-SME EPOT EREA RO R1 R2 RGES S-SNO SI SSM SUZ SLZ 2003 1 1 1 0.385 0.456 0.021 0.000 0.000 0.000 0.013 0.223 0.235 0.01 0.38

I am working with data from the USGS with data every 30 minutes from 4/27/2011 to 8/25/2011. I am having trouble with setting the frequency. My R script is below: > shavers=read.csv("shavers.csv") > names(shavers) [1] "agency_cd" "site_no" "datetime" "tz_cd" "Temp" [6] "X04_00010_cd"

Hi all,  I have a matrix as given below... year month day prec 1   1980    10   1 13.4 2   1980    10   2  0.0 3   1980    10   3  0.0 4   1980    10   4  0.0 5   1980    10   5  0.0 6   1980    10   6  0.0 7   1980    10   7  0.0 8   1980    10   8  0.0 9   1980    10   9  0.0 10  1980    10  10  0.0 11  1980    10  11  7.4 12  1980    10  12  5.4 13  1980    10  13  7.2 14  1980    10  14  0.0

Hello R-users, Checking the archives, I recently came across this topic: "export tables to Excel files" (http://r.789695.n4.nabble.com/export-tables-to-Excel-files-td1565679.html#a1565679), and the following interesting references have been proposed: http://rwiki.sciviews.org/doku.php?id=tips:data-io:ms_windows

R version 2.12.0, 64 bit on Windows. Here is a short script that illustrates the problem: library(tseries) library(xts) setwd('C:\\cygwin\\home\\Ted\\New.Task\\NKs-01-08-12\\NKs\\tests') x = read.table("quotes_h.2.dat", header = FALSE, sep="\t", skip=0) str(x) y <- data.frame(as.POSIXlt(paste(x$V2,substr(x$V4,4,8),sep=" "),format='%Y-%m-%d

Hello everyone, I am just a tyro in R and would like your kindly help for some problems which I've been struggling for a while but still in vain. I have a time-series file (with some missing value ) which looks like time[sec] , Factor1 , Factor2 00:00:00 01.01.2007 , 0.0000 , 0.176083 01:00:00 01.01.2007 , 0.0000 , 0.176417 [ ... ] 11:00:00 10.06.2007 , 0.0000 , 0.148250 12:00:00 10.06.2007