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SF2943 Time Series Analysis
This page contains data and Matlab files for the
project work in SF2943 Time Series Analysis, spring semester 2013.
A.2.1 uses the following files
The data is found in sealevel.mat
or sealevel.dat
and sldate.dat.
A.2.2 uses the following files
- armaacvf.m (autocovariance function for ARMA process)
- arroots.m (computes roots of AR generating function)
- causal.m (tells if the process is causal)
- innov.m (innovation algorithm used in predarma)
- predarma.m (prediction of ARMA process)
- psi.m (psi coefficients in linear representaton)
- roots2ar.m (computes AR parameters from generating function roots)
- simarma.m (simulation of ARMA process)
The functions acf.m and acvf.m will also be needed. The m-file
plotbar.m can be helpful when
drawing autocorrelation functions as bars from the x-axis.
It is similar to the standard m-file stem which draws bars
ending with circles.
B.2.1 uses the following files
- boxcox.m (graph that shows Box-Cox transformation)
- boxcoxf.m (function of Box-Cox transformation)
- pacf.m (Partial autocorrelation function, PACF)
- pergram.m (periodogram)
- specarma.m (spectral density ARMA process)
- specdens.m (spectral density stationary process)
- yuwaest.m (Yule-Walker estimation, AR-process)
The data are found in,
temp.dat,
timech.dat and
el.dat,
or all together in the MATLAB data file
data3.mat.
The matlab command 'load data3' will load them into a MATLAB session.
B.2.2 uses the following files
The MATLAB data file is found in
logret_DEM_USD.mat or
logret_DEM_USD.dat.
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