[R] Time series Regression with lags
Hi, I am working on zoo (time series) objects. Is there any way to do a time series regression with a lag period? E.g., Y(t) = b1*X1(t)+b2*X(t-1)+b3*X2(t) Is "dynlm" the default one to use? Anything else Thanks! [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] R - Time Series Regression with a p-value check for each additional added point.
Hi All, Here is my sample data set.. y x 7/4/2009 -0.2368 -1.2727 7/11/2009 -0.5039 -5.2805 7/18/2009 -0.6655 -6.9641 7/25/2009 -0.3936 -3.6937 8/1/2009 -0.3463 -5.6457 8/8/2009 -0.3000 -1.7368 8/15/2009 0.2378 6.4600 8/22/2009 -0.2962 -3.1113 8/29/2009 -0.4346 -4.2039 9/5/2009 -0.6971 -7.8216 9/12/2009 -0.1217 5.1446 9/19/2009 -0.3107 2.0862 9/26/2009 -0.1797 -3.6055 10/3/2009 0.2299 -0.7373 *10/10/2009 0.4098 -10.1939* When graphed on a scatter plot the bold faced data point significantly reduces the robustness of my regression model. Question, is there a way in R to run a p-value check on each added data point. So lets say given the range of 7/4/2009- 10/03/2009 my p-value was .01; but then after adding 10/10/2009 to the data set my p-value increased to 0.4. At this point a conditional statement could be made saying IF(p-value increase > z) then stop regression at prior date. Thanks for your help, Rick [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] time series regression
Hi Everyone, I am doing a time series regression (one dependent time series variable, 7 independent time series variables and 32 annual observations). I have the problem of cointegration, autocorrelation and multicollinearity. I am considering an error correction model of the form: diff(lnY(t))=a+b1*lnY(t-1)+b2*lnX(t-1)+b3*diff(lnX(t))+error and not able to solve all problems. Any suggestion how to built a good model that solves these problems? I appreciate your help. Thanks, Bereket [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] time series regression
Dear, I am doing a time series regression (one dependent time series variable, 7 independent time series variables and 32 annual observations). I have the problem of cointegration, autocorrelation and multicollinearity. I am considering an error correction model of the form: diff(lnY(t))=a+b1*lnY(t-1)+b2*lnX(t-1)+b3*diff(lnX(t))+error and not able to solve all problems. Any suggestion how to built a good model that solves these problems? I appreciate your help. Thanks, Bereket [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] time series regression
Hi Everyone, I am trying to do a time series regression using the lm function. However, according to the durbin watson test the errors are autocorrelated. And then I tried to use the gls function to accomodate for the autocorrelated errors. My question is how do I know what ARMA process (order) to use in the gls function? Or is there any other way to do the time series regression in R? I highly appreciate your help. Thanks, Bereket [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
