On 26/07/2008 7:40 AM, Fotis Papailias wrote:> Dear R-users,
>
> I have sent another mail some hour ago about a matlab Code I was trying to
> translate in R.
>
> Actually I have found a simpler code originally written in S-PLUS for the
> same function.
> Author's page -> http://math.bu.edu/people/murad/methods/locwhitt/
>
> ============================================================>
> rfunc_function(h, len, im, peri)
> # h -- Starting H value for minimization.
> # len -- Length of time series.
> # im -- Use only len/im frequencies.
> # peri -- Periodogram of data.
> {
> m <- len %/% im
> peri <- peri[2:(m + 1)]
> z <- c(1:m)
> freq <- (2 * pi)/len * z
> result <- log(sum(freq^(2 * h - 1) * peri)) - (2 * h)/m *
> sum(log(freq)
> ) # cat("H = ", h, "R = ",
result, "\n")
> drop(result)
> }
>
>
> locwhitt_function(data, h = 0.5, im = 2)
> # data -- Time series.
> # h -- Starting H value for minimization.
> # im -- Use only N/im frequencies where N is length of series.
>
> {
> peri <- per(data)
> len <- length(data)
> return(nlminb(start = h, obj = rfunc, len = len, im = im, peri >
peri)$
> parameters)
> }
> ==============================================================>
> The author who has written the above S-PLUS code uses two functions (with
> the locwhitt_function he lets the user to define the data and the
parameters
> and with the rfunc_function he does the minimization.)
>
> Mine translation is in R is:
>
> where I use a joint function compared to the the above author
>
>
> ===============================================================>
> lw <- function(x, d, im)
> {
> peri1 <- per(x)
> len <- length(x)
> m <- len/im
> peri <- peri1[2:(m+1)]
> z <- c(1:m)
> freq <- ((2*pi)/len) * z
> result <- log(sum(freq^(2*d-1)*peri))-(2*d)/m * sum(log(freq))
> }
>
> ================================================================>
> which seems to run ok.
>
> But when I do
>
> k <- optimize(lw, x, im=2, interval=c(0, 0.5))
>
> I always get the same result no matter the (simulated) data in x!
>
> The parameter of interest to be minimized is "d". Does anyone
know how to
> edit the function "optimize" so it can work properly?
optimize() is fine, but the way you're calling it is not. It optimizes
a function over the first argument. So you could rewrite lw to put d
first, or write a new function which calls it, e.g.
target <- function(d) lw(x, d, im)
and then
optimize(target, interval=c(0, 0.5))
Because target is defined in the global environment, it will look there
for x and im, and you don't need to pass them as arguments: unless x
and im aren't defined there too!
Duncan Murdoch