A few ideas:
Make a log-scale y-axis like:
hist(my.data,...,log="y")
argument yaxp can help make the ticks look pretty...see ?par.
Or use various functions from the package `plotirx': axis.break and
gap.barplot might be helpful.
For those functions, you'll probably need to get your frequencies
the error:
Error in as.vector(.Call("RS_fractal_bootstrap_circulant_embedding", S, :
error in evaluating the argument 'x' in selecting a method for function
'as.vector'
If I am missing other useful functions for producing/estimating time series
of the fractional/long-
; 1 2 3 4
> >> rollapply(zoo(x), 2, sum)
> > 1 2 3
> > 3 5 7
> >> rollapply(zoo(x), 3, sum)
> > 2 3
> > 6 9
> >> rollapply(zoo(x), 4, sum)
> > 2
> > 10
> >
> > # all at once
> > sapply(1:4, function(r) rollapply(zoo(x)
Hello,
I'd like to take all possible sub-summands of a vector in the quickest and
most efficient way possible. By "sub-summands" I mean for each sub-vector,
take its sum. Which is to say: if I had the vector
x<-1:4
I'd want the "sum" of x[1], x[2], etc. And then the sum of x[1:2], x[2:3],
etc
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