similar to: Running R from windows command prompt

Folks, Is there any implementation available in R for the simultaneous selection of lag order and rank of a nonstationary VAR as described in Chao & Phillips (1999): Model selection in partially nonstationary vector autoregressive processes with reduced rank structure, J. Econ. (91). Or any other systematic procedure for the consistent selection of lag order and cointegration rank? I

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]]

This happened two or three weeks ago and it's happening again. Spammers are using Nabble to attack R-Help. The psts are signed radhi and the posts' titles are taken from previous posts and therefore seem authentic but all messages end with "click here". I suggest you don't. And don't rply to this "radhi" And again on a weekend. Rui Barradas

I am new in R. Can anyone tell : 1. how we can write our own functions in R ? 2. how we can save those functions and recall to use them? 3. what extensions are used for saving a file? -- Siddharth Arun, 4th Year Undergraduate student Industrial Engineering and Management, IIT Kharagpur [[alternative HTML version deleted]]

How we can call auto.arima in R. Is there any cran package we need to install for this function? -- Siddharth Arun, 4th Year Undergraduate student Industrial Engineering and Management, IIT Kharagpur [[alternative HTML version deleted]]

Hello, I'm using fArma package to estimate the value of Hurst exponent using R/S method. However, for a certain set of data I get H ~ 1.8. How do I interpret this? Following are the output that I get for this set: > mean(data[,2]) [1] 400.5433 > sd(data[,2]) [1] 1139.786 > > rsFit(data[,2], levels = 64) Title: Hurst Exponent from R/S Method Call: rsFit(x = data[, 2], levels

I am using auto.arima() for forecasting.When I am using any in built data such as "AirPassangers" it is capturing seasonality. But, If I am entering data in any other format(in vector form or from an excel sheet) it is not detecting seasonality. Is there any specific format in which it detects seasonality or I am doing some thing wrong? Does data have to be entered in a specific

Dear members, I estimated a vector error correction model (VECM) using the "ca.jo" function in package "urca". I need to simulate the estimated model using R. I am aware how to simulate a VAR(p) model. Since the VECM is in difference form, I can't modify the VAR simulation codes to VECM. May one help me in this regard please? Thanks Mamush [[alternative HTML version

Hi All, a) Is it possible to estimate the strength of seasonality in timeseries data. Say I have monthly mean prices of an ten different assets. I decompose the data using stl() and obtain the seasonal parameter for each month. Is it possible to order the assets based on the strength of seasonality? b) which gives a better estimate on seasonality stl() or a robust linear model like

HI everyone, I''m trying to assign colors to multiple lines in a graph. Problem is I don''t want to type in as many colors as there are lines....is there a way around this? In brief, I''m plotting the logratio for up to 60 samples and want a different color for each sample. Here is the code I''m using now.. Any help is greatly appreciated.. Best LT data <-

Hello, I'm an absolute beginner with R. I'm hoping to do some time-series analysis on my data. The data looks like #time value 18 153 20 426 70 7 83 130 84 7 and so on where time could be in seconds or hours or days (not all at the same time). How could I import such a file to R and do some simple stuff (say plot the values)? As per the tutorials on time series, I could use the ts()

Hi, everyone, I currently run into a problem about DCC-Garch model. I use the package cc-garch and the function dcc.estimation. One of the output of this function is DCC matrix, which shows conditional correlation matrix at every time period you gives. However, I cannot figue out how the function calculate the conditional correlation matrix at the first time period, since there is no data to be

i am new to time series,whatever i know up till now,from that i have uploaded time series file & what to build arma model,but for that i want p & q values(orders) tell me how to calculate best p & q values to find best AIC values for model i am doing but giving error >bhavar<-read.table(file.choose()) #taking time series file > decompose(bhavar$V1) Error in

I am using AUTO ARIMA for forecasting. But it is not detecting 'seasonality term' of its own for any data. Is there any other method by which we can detect seasonality and its frequency for any data? Is there any method through which seasonality and its frequency can be automatically detected from ACF plot? -- Siddharth Arun, 4th Year Undergraduate student Industrial Engineering and

I was using tagPOS function from openNLP package for parts-of-speach. Now the package is updated and the function is not present. Any suggestions how to do it now ? Thanks for your help. -- Regards, Siddharth Arun, Contact No. - +91 8880065278 [[alternative HTML version deleted]]

Hello, I'm using the fArma package to estimate Hurst exponent by R/S method. I've some measurements in the following format: Call_number Call_duration I'm using the following steps. Am new to R, so it would help if someone could please confirm if my steps are correct. Further, this method seems to give a value H ~= 0.8 (> 0.5). Is the use of R/S method to estimate H OK? >

Dear r-users, Suppose I have two data sets data set-1 Date height ------------------------ 1/11/2005 10 2/11/2005 23 3/11/2005 54 4/11/2005 21 5/11/2005 22 data set-2 weight -------- 32 45 11 Now I want to combine this two data sets. i.e. i want to see: Date height weight ------------------------------------------- 3/11/2005 54

Dear aDVISOR, Hope I am not disturbing you. Can you tell me how I can perform Multivariate Garch analysis in R. Also please, it is my humble request let me know some resource materials on Multivariate Garch analysis itself. Sincerely yours, -- Arun Kumar Saha, M.Sc.[C.U.] S T A T I S T I C I A N [Analyst] Transgraph Consulting [www.transgraph.com] Hyderabad, INDIA Contact # Home:

Dear all R users, I want to insert the R logo in every graphic that I made in my Statistical analysis using R. Can anyone tell me whether is it possible or not and if possible how to do this? your help will be highly appreciated. Thanks and Regards, Arun [[alternative HTML version deleted]]

Dear all, I have a variable 'x' like that: > x [1] "2005-09-01" Here, 2005 represents year, 09 month and 01 day. Now I want to create three variables naming: y, m, and d such that: y = 2005 m = 09 d = 01 can anyone tell me how to do that? Regards, [[alternative HTML version deleted]]