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The
library also contains some data sets. All of the major functions and
the data sets are fully documented with help files. The reference below
should be cited, when the library ellipticalhet had been used.
Please click on the appropriate link for the section and version
you require.
 R symarma.zip written
in R 2.13.0
How to install the library
The single library sections are zip files.
Expand the archives and follow then the instructions in the INSTALL
file to complete the installation of the library. If all library
sections are to be installed, it is best to create a main directory
elliptical which will contain the library sections. Copy the Zip files
to the corresponding directories before unpacking them.
You should then follow the instructions above
for each library section. The README
file for the whole library. Save it in the main directory ELLIPTICALTS.
Once this is done, and once inside S-PLUS or R in your usual working
directory, the functions and data are accessed by typing command “source”
Examples
One example is used to
explain library and can script
in R and dataset can be founded here.
We
consider the time series of excess return in the daily closing prices
on Microsoft and the S&P 500 index. The S&P 500 was taken as
the market price. This series consists of n=109 observations from April
1, 2002 to September 5, 2002. The Microsoft's excess returns (Y_t) and
the excess market return (X_t) were defined as Y_t =
r_t - r_{ft} and X_t = r_{mt} - r_{ft} where r_t is the return.
The
return is defined as r_t = (p_t - p_{t-1})/p_{t-1} where p_t is the
price of an asset at time t of Microsoft over a holding period t,
r_{ft} is the risk-free return over the t-th period evaluated by T-bill
rates. The T-bill rates were divided by 100 to convert from a
percentage and then by 253 to convert to a daily rate and r_{mt} is the
market return measured by S&P 500 index.
Fitted
Model AR(1) under symmetrical distribution
Y_t
= \beta X_{t} + \phi\{Y_{t-12} - \beta X_{t-12}\} + r_t,
t = 13,...,109.
A
brief description of the complete dataset can be found in Ruppert (2004, p.239). Ruppert,
D. (2004) Statistics and
Finance. New York: Springer.
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