AR is just OLS, so you should be able to do
(X' * X) \ X' * Y
with the right X and Y matrices.
Note the difference between * and .* OLS is a matrix expression, not a
element-wise operation.
Start by making sure that the X and Y matrices look like you expect them
to, shape-wise and content-wise.
Regarding the TimeSeries package, I can't test my hunch right now, but I
suspect it's because 0 and 0.0 are different in Julia. One's an Integer and
the other's a Float. Same with 1 and 1.0 My guess is that the TimeSeries
function needs Float arguments and you pass it Integers.
On Thursday, January 1, 2015 7:58:05 PM UTC-5, jspark wrote:
>
> Hi,
>
> Now I become a two weeks old for Julia and still struggling with Julia.
>
> I am porting *AR1 function* below from a *cran R* but for some reason it
> gives me an error (SingularException(3)) when I convert *solve() to get
> Alpha* into *inv()*. However, it works with R and Matlab.
>
> y=float(r,1]) # r is data vector from the attached DJ.csv file
>
> T = length(y)-1;
>
> Y = y[2:T]';
>
> Y1= y[1:(T-1)]';
>
> Alpha= inv(Y1'.*Y).*(Y1').*Y;
>
>
> *ERROR : SingularException(3)*
>
> As an alternative, I am trying to get AR1 coefficient from *arima() *of
> the *TimeModels* package but it's not working either.
>
> using TimeModels
>
> zz=rand(500,1); #500*1 Array(Float64,2)
> arima(zz,1,0,0);
>
> *ERROR : 'arima' has no method matching arima (::Array{Float64,2),
> ::Int64, ::Int64, ::Int64)*
>
> Can someone tell me what is the behind story of the error?
>
> Many thanks and Happy New Year to all!!
>
>
> AR1 <-function(x){T <- length(x) -1Y <- x[2:T]Y_ <- x[1:(T-1)] ALPHA <-
> solve(t(Y_) %*% Y_ ) %*% t(Y_) %*% YRE <- Y - Y_ %*% ALPHASIGMAS <- sum(RE
> ^2) / (T-1)STDA <- sqrt( SIGMAS * solve(t(Y_) %*% Y_ ))return(list(ALPHA=
> ALPHA,STDA=STDA))} Source : ttps://
> github.com/cran/vrtest/blob/master/R/AR1.R
>
>
