Hello.
I have got two problems in bootstrapping from
dependent data sets.
Given two time-series x and y. Both consisting of n
observations with x consisting of dependent and y
consisting of independent observations over time. Also
assume, that the optimal block-length l is given.
To obtain my bootstrap sample, I have to draw
pairwise, but there is the problem of dependence of
the x-observations and so if I draw the third
observation of y, I cannot simply draw the third
observation of x (to retain the serial correlation
structure between x and y), because I devided x into
blocks of length l and I have to draw blocks, then I
draw from x.
1.
How can I compute a bootstrap sample of the
correlation coefficient between x and y with respect
to the dependence in time-series of x?
2.
How does it look like, if x and y both consist of
dependent observations?
I hope you can help me. I got really stuck with this
problem.
Sincerly
Klein.