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A Guide to Ingres: A User's Guide to the Ingres Product by C. J. Date

By C. J. Date

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8 shows two histograms. 2 First Exploratory Data Analysis Tools 15 Fig. 8. Examples of histograms: PCS index (left) and S&P weekly log-returns (right). index) > hist(WSPLRet) > par(mfrow=c(1,1)) The first command is intended to divide the plotting area into a 1 × 2 matrix in which plots are inserted in sequence. The next two commands actually produce the histograms. index and WSPLRet whose creation was explained earlier. Histograms are produced in S-Plus with the command hist. See the help file for details on the options available, including the choice of the number of bins, their size, .

See the help file for details on the options available, including the choice of the number of bins, their size, . . The fourth command restores the default option of one plot per screen. The histogram on the left is for the PCS data which we introduced earlier, and which we will study in detail later in this chapter. Obviously, there are no negative data points (something we could have expected based on the meaning of the data) and the bulk of the data is concentrated near 0. The histogram on the right is for the weekly log-returns on the S&P 500 index.

We illustrate the details of this random generation procedure on the example of the Cauchy distribution. Example. 11). 12). As explained earlier, this distribution belongs to the family of generalized Pareto distributions (for which we use the abbreviation GDP) which we will introduce later in our discussion of heavy tail distributions. 2. S-Plus commands for the manipulation of the classical probability distributions. 5)) will produce a vector CAUCHY of length N of Cauchy variates with location M and scale parameter LAMBDA.

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