similar to: how to use VARselect with missing values - beginner's question

Hi all,   I have 5 series  (5 ts objects: rp, igpm, ereal, jurosreal, crescpib), and want to create a vector with the means of the last values of each variable. What I did was this:   mrp1<-mean(tail(rp,9)) migpm1<-mean(tail(igpm,9)) mereal1<-mean(tail(ereal,9)) mjr1<-mean(tail(jurosreal,9)) mcp1<-mean(tail(crescpib,9)) means=rbind(mrp1,migpm1,mereal1,mjr1,mcp1)   They are monthly

I am working on Johansen cointegration test, using urca and var package. in the selection of var, I have got following results. >VARselect(newd, lag.max = 10,type = "none") $selection AIC(n) HQ(n) SC(n) FPE(n) 6 6 6 5 $criteria 1 2 3 4 5 6 7 8 9 AIC(n) -3.818646e+01 -3.864064e+01

Hello to everyone! I am working on my final year project about multivariate time series. There are three variables in the multivariate time series model. I have a few questions: 1. I used acf and pacf plot and find my variables are nonstationary. But in adf.test() and pp.test(), the data are stationary. why? 2.I use VAR to get a model. y is the matrix of data set and I have made a once

thank you for your valuable reply. I have attached my commands, results, and data with this mail..maybe it will be beneficial for you to feedback. On Tue, Nov 21, 2017 at 9:13 PM, Jeff Newmiller <jdnewmil at dcn.davis.ca.us> wrote: > Your example is incomplete... as the bottom of this and every post says, > we need to be able to proceed from an empty R environment to wherever you

Your example is incomplete... as the bottom of this and every post says, we need to be able to proceed from an empty R environment to wherever you are having the problem (reproducible), in as few steps as possible (minimal). The example needs to include data, preferably in R syntax as the dput function creates... see the howtos referenced below for help with that. [1], [2], [3] You also need to

Hi, Could someone please tell me the R codes for fitting VAR(p) (Vector Auto Regressive) models and doing the Johansen?s cointegration tests. TIA Aditya

Hello I am running var on dataset data1 is the name of my dataset cn.chf us.chf 2005-07-01 -1.18656633 -1.18656633 2005-07-04 -0.48835920 -0.48835920 2005-07-05 -0.01534272 -0.01534272 2005-07-06 0.08825279 0.08825279 2005-07-07 0.34223563 0.34223563 2005-07-08 -0.05776229 -0.05776229 commands which I am usings are 1) lag.var <- VARselect(data1, 10,

Folks, I have been using the VAR {vars} program to find a fit for the following bi-variate time series (subset): bivariateTS<-structure(c(0.950415958293559, 0.96077848972081, 0.964348957109053, 0.967852884998915, 0.967773510751625, 0.970342843688257, 0.97613937178359, 0.980118627997436, 0.987059493773907, 0.99536830931504, 1.00622672085718, 1.01198013845981, 1.01866618122606,

Hello, I'm using VAR models in R in order to obtain impulse responses of stock market shock on US economy. I have series of quarterly changes in real gdp, S&P 500 and quarterly level of unemployment for 1985 - 2012 period. My series are stationary. So I did all the steps below. However I don't understand what do irf function results mean. These are the cumulative orthogonal responses

Dear R Users, Can someone point me to a R package which will help me optimally choose a lag for Granger Causality testing ? Many thanks in advance, Tolga Generally, this communication is for informational purposes only and it is not intended as an offer or solicitation for the purchase or sale of any financial instrument or as an official confirmation of any transaction. In the event you are

Thank you for reading. I am trying to get sphericity values, and I understood I need to use mlm, but how do I implement a nested within subject design in mlm? I already read the R newsletter, fox chapter appendix, EZanova, and whatever I could find online. My original ANOVA anova(aov(resp ~ sucrose*citral, random =~1 | subject, data = p12bl, subset = exps==1)) Or anova(aov(resp ~