similar to: multiple tests: t-statistic for vectors in 4-dimensional array

Hola everyone, Solving this issue would be a huge time saver for analyzing my thesis data, so I'll try to be as concise as possible and hope that someone can give me a hand. I am trying to run a function that I created, which works fine until I try to use it with the by function. That function is listed at the bottom (f3) just in case that might be the issue. Essentially I have compiled a

Dear R users, I am trying to fill in arrays (5 different according to distinct "id") from objects produced from arbitrary data set below. a <-

I know there are a lot of reshape questions on the mailing list, but I haven't been able to find an answer to this particular issue. I am trying to get a datafame structured like this: > sub <- rep(1:5) > ta1 <- rep(1,5) > ta2 <- rep(2,5) > tb1<- rep(3,5) > tb2 <- rep(4,5) > DF <- data.frame(sub,ta1,ta2,tb1,tb2) > DF sub ta1 ta2 tb1 tb2 1

Dear list, I need to convert this data.frame > names(codesM) [1] "key" "AMR.pa1.M" "AMR.pa2.M" "AMR.pa3.M" "AMR.pa4.M" [6] "AMR.pa5.M" "AMR.pa6.M" "AMR.pa7.M" "AMR.pa8.M" "AMR.pa9.M" [11] "AMR.pa10.M" "AMR.ta1.M" "AMR.ta2.M" "AMR.ta3.M"

Hi all R-users, I?m trying to assign colors on those p-value in my table output that fall above a certain critical value, let?s say a p-value >0.05. My table looks like this: Assets ADF-Level P-Value ADF-First D P-Value ADF-Second D P-Value [1,] Liabilities -2.3109 0.1988 -3.162 0.025 -6.0281

hi there, i have posted earlier on the list but got no satisfying answer. the problem is not big. I have asterisk server directly connected with internet (79.80.x.x) and clients are behind router. clients/users are registered with asterisk and are using sipura and xlite softphone. Now problem is that when a user calls other by dialing his IP:Port (sip uri), call is connected fine and he can

Dear Users, please help with the following DF test: ===== library(tseries) library(timeSeries) Y=c(3519,3803,4332,4251,4661,4811,4448,4451,4343,4067,4001,3934,3652,3768 ,4082,4101,4628,4898,4476,4728,4458,4004,4095,4056,3641,3966,4417,4367 ,4821,5190,4638,4904,4528,4383,4339,4327,3856,4072,4563,4561,4984,5316 ,4843,5383,4889,4681,4466,4463,4217,4322,4779,4988,5383,5591,5322,5404

Dear all: I am having some problems to use the function "sink()". Basically I am doing a loop over two files which contain unit-root variables. Then on a loop, I extract every i element of both files to create an object called z. If z meets some requirements, then I perform a unit root test (ADF test), otherwise not. As this process is repeated several times, for each i I want to get

Short question: Is it possible to use statistical tests, like the Augmented Dickey-Fuller test, in functions with for-loops? If not, are there any alternative ways to scale measures? Detailed explanation: I am working with time-series, and I want to flag curves that are not stationary and which display pulses, trends, or level shifts. >df DATE ID VALUE2012-03-06 1

Hello everybody, I've got a matrix called EUROPEDATA and I want to calculate the adf test statistic (part of the tseries package) on a rolling basis for window my.win on each column; i.e. each column of EUROPEDATA represents a particular variable; for the first column I calculate the adf test statistic for window my.win = 60 for example, roll forward one observation, calculate the adf

Hi all, Hope you people do not feel irritated for repeatedly sending mail on Time series. Here I got another problem on the same, and hope I would get some answer from you. I have following dataset: data[,1] [1] 4.96 4.95 4.96 4.96 4.97 4.97 4.97 4.97 4.97 4.98 4.98 4.98 4.98 4.98 4.99 4.99 5.00 5.01 [19] 5.01 5.00 5.01 5.01 5.01 5.01 5.02 5.01 5.02 5.02 5.03 5.03 5.03

Hi all, I tried to do a Dickey Fuller test with R using adf.test with a time series of german stock prices. I have 10 stocks from 1985 to 2009 with monthly stock prices. So if you do the math I have 289 values for each stock. I tried to do the test for each stock alone and had the 289 values of my first stock listed in R. When I tried to do the test with command adf.test(x, k=1) the following

Hello! I do not understand what is meant by: "aic" and "bic" follow a top-down strategy based on the Akaike's and Schwarz's information criteria in the datails to the ADF.test function. What does a "top-down strategy" mean? Probably the respective criterion is minimized and the mode vector contains the lag orders at which the criterion attains it

I am not able to run Dickey-Fuller test. adf.test() function is not working. It is showing 'Error: could not find function "adf.test" Can any tell how to call "time series" library? -- Siddharth Arun, 4th Year Undergraduate student Industrial Engineering and Management, IIT Kharagpur [[alternative HTML version deleted]]

Dear R gurus, As part of finding initial values for a much more complicated fit I want to fit a function of the form y ~ a + bx + cx^d to fairly "noisy" data and have hit some problems. To demonstrate the specific R-related problem, here is an idealised data set, smaller and better fitting than reality: # idealised data set aDF <- data.frame( x= c(1.80, 9.27, 6.48, 2.61, 9.86,

Hello all, I tried to extract the p-value from adf.test in tseries; however, I got the error message such as > ht=adf.test(list.var$aa) > ht$p-value Error in ht$p - value : non-numeric argument to binary operator > ht Augmented Dickey-Fuller Test data: list.var$aa Dickey-Fuller = -2.3147, Lag order = 4, p-value = 0.4461 alternative hypothesis: stationary > ht$data [1]

Hi all, Can anyone clear my doubts about what conclusions to take with the following what puts of some time series tests: > adf.test(melbmax) Augmented Dickey-Fuller Test data: melbmax Dickey-Fuller = -5.4075, Lag order = 15, p-value = 0.01 alternative hypothesis: stationary Warning message: p-value smaller than printed p-value in: adf.test(melbmax)

Dear R users, I have a function (below) which encompasses several tests. However, when I run it, only the output of the last test is displayed. How can I ensure that the function root(var) will run and display the output from all tests, and not just the last one? Thank you, b. root <- function(var) { #---Phillips-Perron PP.test(var, lshort = TRUE) PP.test(var, lshort = FALSE)

Dear R-help, I have an xts data set that i have subset by date. now it contains a date-time-stamp, and two columns (price and volume traded): my objective is to create tables of volume traded at a price - and i've been successfully using aggregate to do so in interactive use. say the data looks as follows: px_ym1 vol_ym1 2012-06-01 09:37:00 97.91 437 2012-06-01

this command is used in tseries adf.test(x, alternative = c("stationary", "explosive"), k = trunc((length(x)-1)^(1/3))) this command apply adf test on data given in x .here general equatiuon that is, equation with constant and trend is used.if i did not include constant or trend in the equation and run the command then how i can run this command in tseries.