Dear Tom: Your revised function eliminates the discrepancy in the degrees of freedom but is still very different from the numbers reports on Tsay, p. 102:
archTest(log(1+as.numeric(m.intc7303)), lag=12) ARCH test (univariate) data: Residual of y1 equation Chi-squared = 13.1483, df = 12, p-value = 0.3584 Warning message: In VAR(s, p = 1, type = "const") : No column names supplied in y, using: y1, y2, y3, y4, y5, y6, y7, y8, y9, y10, y11, y12 , instead. TOM: What can you tell me about the warning message? Thanks for your help with this. Spencer Graves tom soyer wrote: > Spencer, > > Sorry, I forgot that the default lag in arch is 16. Here is the fix. Can you > try it again and see if it gives the correct (or at least similar compared > to a true LM test) result? > > archTest=function(x, lags=12){ > #x is a vector > require(vars) > s=embed(x,lags) > y=VAR(s,p=1,type="const") > result=arch(y,lags.single=lags,multi=F)$arch.uni[[1]] > return(result) > } > > Thanks and sorry about the bug. > > > On 2/2/08, Spencer Graves <[EMAIL PROTECTED]> wrote: > >> Dear Tom, Bernhard, Ruey: >> >> I can't get that to match Tsay's example, but I have other >> questions about that. >> >> 1. I got the following using Tom's 'archTest' function (below): >> >> >>> archTest(log(1+as.numeric(m.intc7303)), lags=12) >>> >> ARCH test (univariate) >> >> data: Residual of y1 equation >> Chi-squared = 10.8562, df = 16, p-value = 0.8183 >> >> Warning message: >> In VAR(s, p = 1, type = "const") : >> No column names supplied in y, using: y1, y2, y3, y4, y5, y6, y7, y8, >> y9, y10, y11, y12 , instead. >> >> >> ** First note that the answer has df = 16, even though I >> supplied lags = 12. >> >> 2. For (apparently) this example, S-Plus FinMetrics 'archTest' >> function returned "Test for ARCH Effects: LM Test. Null Hypothesis: >> no ARCH effects. Test Stat 43.5041, p.value 0.0000. Dist. under Null: >> chi-square with 12 degrees of freedom". >> >> 3. Starting on p. 101, Ruey mentioned "the Lagrange multiplier >> test of Engle (1982)", saying "This test is equivalent to the usual F >> test for" no regression, but refers it to a chi-square, not an F >> distribution. Clearly, there is a gap here, because the expected value >> of the F distribution is close to 1 [d2/(d2-2), where d2 = denominator >> degrees of freedom; http://en.wikipedia.org/wiki/F-distribution], while >> the expected value for a chi-square is the number of degrees of freedom >> >> Unfortunately, I don't feel I can afford the time to dig into this >> further right now. >> >> Thanks for your help. >> Spencer Graves >> >> tom soyer wrote: >> >>> Spencer, how about something like this: >>> >>> archTest=function (x, lags= 16){ >>> #x is a vector >>> require(vars) >>> s=embed(x,lags) >>> y=VAR(s,p=1,type="const") >>> result=arch(y,multi=F)$arch.uni[[1]] >>> return(result) >>> } >>> >>> can you, or maybe Bernhard, check and see whether this function gives >>> the correct result? >>> >>> thanks, >>> >>> On 2/1/08, *Spencer Graves* <[EMAIL PROTECTED] >>> <mailto:[EMAIL PROTECTED]>> wrote: >>> >>> Hi, Tom: >>> >>> The 'arch' function in the 'vars' package is supposed to be >>> >> able >> >>> to do that. Unfortunately, I was unable to make it work for a >>> univariate series. Bernhard Pfaff, the author of 'vars', said >>> that if I >>> read the code for 'arch', I could easily retrieve the necessary >>> >> lines >> >>> and put them in my own function; I have not so far found the time >>> >> to >> >>> try that. If you do, or if you get a better answer than this, >>> would you >>> please let me know? I would like to have this capability for the >>> 'FinTS' package, and I would happily write a help page if someone >>> would >>> contribute the function -- or use a function in another >>> >> package. Tsay >> >>> (2005) Analysis of Financial Time Series, 2nd ed. (Wiley) includes >>> >> an >> >>> example on p. 103 that could be used for a reference. >>> >>> Hope this helps. >>> Spencer Graves >>> >>> tom soyer wrote: >>> > Hi, >>> > >>> > Does anyone know if R has a Lagrange multiplier (LM) test for ARCH >>> > effects for univariant time series? >>> > >>> > Thanks! >>> > >>> > >>> >>> >>> >>> >>> -- >>> Tom >>> > > > > ______________________________________________ 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.