An ECM is very different from an OLS. see Enders, Applied Time Series Analysis for a nice practical discussion. See Hamilton , Time Series Analysis fora more theoretical discussion.

<r>if that functions comes from the add on SplusFinmetrics ( or maybe even if it doesn't ), a good person to ask would be eric zivot or youshould join the Splus Newsgroup. Someone on that list might know but Eric would be the best to ask. i think his email is <EMAIL email="e.zivot@washington.edu">e....

<t>what the person said about 2 parameters and letting one go to infinity is fine but in regard to what you said,the expression for a weiner process isds = u*dt + sigma*dw = u*dt + sigma*epsilon*radical t ( discretizing the brownian motion where epsilon is normal(0,1) ).so, the variance is sigma^2* ...

<t>i'm not definite on this but i'll give it a shot. the total number of ways you can pick 3 cards from the deck is 52 choose 3 = 52*51 *50.the number of ways each card can be a different suit is 4*3*2 = 24the number of ways each card is not consecutive and not the same is : well, the first card has...

box and jenkins : time series analysis is the bible.also, a more upto date all encompassing time series book : hamilton : time series analysis.

i think the answer to b in is in michael steele's probability book, the title of which escapes me at the moment ( justgo to amazon and type in his name ) . the rest may be in there somewhere also.

<t>There are tests of H_o : Covariance matrix is diagonal versus H_1 : Covariance matrix is some other specifiedform. I think these should be in Greene or Kennedy. But I am unsure and doubt if there are tests of H_o : Covariance matrix is diagonal versus H_1 : Covariance matrix is not diagonal.if yo...

<t>R = SRvol1 + rf, SRvol2 + rf SRvol3 + rf . . . SRvoln + rfand you want to maxT= (w'R - rf)/sqrt(w'Vw) - Lamba(1-w'I) wrt wSo, since R is the same for each, I think ( check this ) thatT simplifies to SR*(w'R*)/sqrt(w'V'w) - Lamba(1-w'I) where R* = vol1 + rf/SR vol2 + rf/SR . . . . . voln + rf/SRMa...

<t>you are assuming generalized least squares where thecovariance matrix is not diagonal ( like it is OLS ) so the estimateof the covariance matrix will be epsilon hat times esplion hat prime which is n by 1 times 1 by n = n by n. epsilon hat isis the estimated residual vector.gls is not as straight...

<r>I think you are using windows. in that case, try the other typeof backslash and 2 of them each time. I think that shouldwork. Also, go to <URL url="http://www.r-project.org">www.r-project.org</URL> because thereis a great r-help newsgroup that you can join where questions like yours willbe answer...

<t>cointegration with a fixed cointegrating vectoris a DF test ( on the residuals generated from the fixed cointegrating relationship ) so it sounds like they are doingthe DF test twice ? I'm not sure whatyou are reading but, if you let me know,I may have read it so I might be able to give you abett...

<t>does anyone have or know how i can obtainthe following 2 papers ( I can pay some amount ) ?Sharpe, W. F. (1988) Determining the Fund's Effective Asset Mix. Investment Management Review, November - December, 59-69.Sharpe, W.F. (1992) Asset Allocation: Management Style and PerformanceMeasurement, J...

<t>there is no "general technique"for arbitrary distriibutionsbut techniques can be appliedonce the distribution isgiven, depending on what the distribution is.the sum can be simple forcertain distributions ( normal, exponential )and the sum of the squared can alsobe simple for certain distributions...

<t>one way would be use to a kalman filterapproach ( see andrew harvey's blue book,i forget title )and model the series using his "basic structural model" ( bsm ).this type of model imposes "sum constraints" sort ofautomatically.if you aren't familar with thekalman filter/dlms, it'sprobably not wort...

the problem is not so difficult ifthe marginals are normalor uniform ( atleastfor the bivariate case but maybe beyond bivariate , it is also difficult ) but, for other distributions besides those two, i am unawareof a general technique.