This has been solved, and I'm thankful for the help. The solution is: z = MyModel$coef/diag(MyModel$var.coef)
...and from there I will use a for loop and pnorm to get the p-values. Thanks again! Byron zerfetzen wrote: > > This should be very easy, but alas, I'm very new to R. My end goal is to > calculate p-values from arima(). > > Let's say I just ran this: > >> MyModel <- arima(y[1:58], order=c(1,0,0), xreg=MyData[1:58,7:14], >> method="ML") >> MyModel > > And I see: > > > arima(x = y[1:58], order = c(1, 0, 0), xreg = MyData[1:58, 7:14], method = > "ML") > > Coefficients: > ar1 intercept x1 x2 x3 x4 x5 > x6 > 0.5812 -52.7725 -0.0270 -6.3467 2.8435 4.3727 -14.9045 > -3e-04 > s.e. 0.1328 16.6182 0.0212 3.6454 1.5571 0.5641 2.4294 > 2e-04 > x7 x8 > 2.4094 1.0823 > s.e. 0.5134 0.3093 > > sigma^2 estimated as 1.223: log likelihood = -88.35, aic = 198.71 > > > To calculate a p-value, all I have to do is: > > 1. Let z = parameter / s.e. > 2. Let abs_z = abs(z) > 3. Let p = 1 minus the integral of a normal distribution from -abs_z to > abs_z > > How do I extract the coefficients and standard errors out of the MyModel > object, and place them in their own data frame? From there, I'm sure I > could calculate the p-value. > > I have found that: > >> coef(MyModel) > > ...shows the coefficients, but I'm unable to get them into a data frame. > I tried: > >> MyParameters$coef <- coef(MyModel) > > But when I try... > >> MyParameters <- edit(MyParameters) > > ...I don't see what I would expect: a column of coefficients. And I don't > know how to refer to the standard errors. Help? Thanks. > -- View this message in context: http://www.nabble.com/How-to-extract-vectors-from-an-arima%28%29-object-and-into-a-data-frame--tp16757321p16758220.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.
