outputs the amplitude variables (A_nn _mm ) of the cross-spectrum.

subtracts the series mean before performing the Fourier decomposition. This sets the first periodogram ordinate to 0 rather than 2n times the squared mean. This option is commonly used when the periodograms are to be plotted to prevent a large first periodogram ordinate from distorting the scale of the plot.

specifies that the quadrature spectrum estimate is computed at the boundaries in the same way as the spectral density estimate and the cospectrum estimate are computed.

outputs the Fourier cosine and sine coefficients of each series.

is used with the P and S options to output cross-periodograms and cross-spectral densities when more than one variable is listed in the VAR statement.

names the SAS data set that contains the input data. If the DATA= option is omitted, the most recently created SAS data set is used.

outputs the squared coherency variables (K_nn _mm ) of the cross-spectrum. The K_nn _mm variables are identically 1 unless weights are given in the WEIGHTS statement and the S option is specified.

names the output data set created by PROC SPECTRA to store the results. If the OUT= option is omitted, the output data set is named by using the DATAn convention.

outputs the periodogram variables. The variables are named P_nn, where nn is an index of the original variable with which the periodogram variable is associated. When both the P and CROSS options are specified, the cross-periodogram variables RP_nn_mm and IP_nn_mm are also output.

outputs the phase variables (PH_nn _mm) of the cross-spectrum.

outputs the spectral density estimates. The variables are named S_nn, where nn is an index of the original variable with which the estimate variable is associated. When both the S and CROSS options are specified, the cross-spectral variables CS_nn _mm and QS_nn _mm are also output.

prints two tests of the hypothesis that the data are white noise. See the section White Noise Test for details.

Note that the CROSS, A, K, and PH options are meaningful only if more than one variable is listed in the VAR statement.