similar to: see the example and help me

sample report data that i want to forecast quarter quarter_index Revenue 2007 Q1 1 $3,856,799 2007 Q2 2 $4,243,328 2007 Q3 3 $4,930,369 2007 Q4 4 $5,443,579 2008 Q1 5 $5,164,830 2008 Q2 6 $5,104,413 2008 Q3 7

Good morning everyone, I have attached an Excel file that contains a macro from which I call and use R's auto.arima function to generate forecasts. The program runs perfectly and it gets me the results; however, those results are pretty unusual. I also tried using the auto.arima function directly in the R console and still get weird results. The results are shown in columns AB, AC and AD

Hi, Although my doubt is pretty,as i m not from stats background i am not sure how to proceed on this. Currently i am doing a forecasting.I used ARIMA to forecast and time series was volatile i used garchFit for residuals. How to use the output of Garch to correct the forecasted values from ARIMA. Here is my code: ###delta is the data fit<-arima(delta,order=c(2,,0,1)) fit.res <-

Hello, i have been doing browns exponential smooting for myself and have a little trouble with plotting values: par(xpd=TRUE) plot(vector,xlab="Period",ylab="Values") legend(max(vector), legend = c("Original values", "Estimated values"), col=c("blue","red"),lwd=0.5, cex=1, xjust=0.1, yjust=-0.3) lines (vector, type =

Hi, This is regarding the ARIMA model. I am having time series data of stock of 2000 values. Using the ARIMA model in R, I want the forcasted values for next 36 time points. However when I run this model in R, I am getting same value for all 36 time points. I have tried to fit the data with ARIMA model by changing the parameters p,d,q after looking at the errors and other criteria for

MY REQUIREMENT: I have a database and i want to connect to the database through R Project and using the tables from the database i need to generate the reports. can anyone plese tell me whether this is possible with R project or not. Thanks in advance Chinna. -- View this message in context: http://n4.nabble.com/Generating-reports-from-database-tp1564238p1564238.html Sent from the R help

Dear all, I have spent the last few days on a seemingly simple and previously documented rolling regression. I have a 60 year data set organized in a ts matrix. The matrix has 5 columns; cash_ret, epy1, ism1, spread1, unemp1 I have been able to come up with the following based on previous help threads. It seems to work fine. The trouble is I get regression coefficients but need the immediate

Hello, does anyone know of any R routines capable of whats called Hierarchical Forecasting, reconciling the different hierarchies. Example: A top down forecast where the corporate forecast is created and then all the regions within the corporate entity are also forecasted, with the constraint they sum to the corporate forecast.

hi all. i'm busy with some time series data, starting from an earlier period until the current day. i have created a time series forecast taking into account the entire data from the earlier date up until 2007, using the "forecast" package for R. i am comparing this forecasted data to the actual/ observed data (which starts from the earlier date up until the current day). my

Dear R users, i am wondering if anyone has some hints for this problem (i have not found a clear answer after searching the R-mailing list archive, 'help.search' in R, and R-Wiki, and the like...): let's assume that i have 4 periods compositional time series data: t=1, A=0.1; B=0.5; C=0.4 t=2, A=0.2; B=0.4; C=0.4 t=3, A=0.5; B=0.3; C=0.2 t=4, A=0.4; B=0.3;

Hello, I have been using R/S+ for years and love the software. Still a novice but I can do what i need to. Anyway, I am working on a forecasting project and would like to create a script that automates the following steps: order data by X Create groupings 1...N Separate test data set run regression on each group Determine result. (A mathematical formula is run on the forecasted output) Repeat

Hello , i am working in the functional time series using the multivariate time series data(hourly time series data). Sir? i am using FAR model more than one order for which no statistical package is available in R, so for this i convert my data into functional form and obtained the functional principle component and from those FPCA i extract their corresponding? FPCscores. Know i use the VAR model

hi all , has anyone tried to predict a univariate time series by a neural networks packages ? please help me in this problem . I am new in R and I did not found any document that explains this problem. thanks in advance David [[alternative HTML version deleted]]

Dear R Users, I am new to state-space modeling. I am using SSPIR package for Kalman Filter. I have a data set containing one dependent variable and 7 independent variables with 250 data points. I want to use Kalman Filter for forecast the future values of the dependent variable using a multiple regression framework. I have used ssm function to produce the state space (SS)

Dear all, I just have a short question regarding the forecasting of ARIMA models with external regressors. I tried to program a ARX(1) model arx.mod <- arima(reihe.lern, order = c(1, 0, 0), seasonal = list(order = c(0, 0, 0), period = 52), xreg = lern.design, include.mean = TRUE) for which I need to estimate the next (105th) value. Xreg=lern.design is - at this time - 104 rows long. I

Dear R-list, I try to use StructTS for some univariate time series, with a type="BSM". I have two questions: 1-in the "fitted" value of the object, it seems to me that for getting back fitted values, one have to add level, slope and seasonal (or "level" contains already the two other ones) 2-i am really circumspect about the results of "KalmanForecast"

Dear All: Greetings! I am able to produce an "xyplot" in R; But I am not able to put multiple legends on it! So for that matter, I have saved the "xyplot" and reproduced the same using the simple "plot" option. Then using the "legend" option I successfully placed the require text and its corresponding value over it. Now, when I try to copy it as a

I think the code is part of the RTAQ package but is not included in it, as I obtained it from https://r-forge.r-project.org/scm/viewvc.php/pkg/RTAQ/R/HAR_model.R?view=markup&root=blotter&sortby=author&pathrev=1028. It is not my code and I make no claim to other's good work, and apologize if I should even be posting it I am not sure, but in the transform function it allows to

I am working with xts dependent data, and my code is as follows (the problem is explained throughout): dat <- getdat("prices") dat <- read.zoo(dat, sep = "",format="%d/%m/%Y %H:%M", tz="", FUN=NULL, regular=TRUE, header=TRUE, index.column=1, colClasses=c("character", "numeric")) dat <- as.xts(dat)