The REGRESS command calculates a simple multiple linear regression. The optional WEIGHTBY keyword lets you calculate a weighted regression when some of the data points are more reliable than others.
You can then execute REGRESS.REPORT to produce a standard report of the regression. You can also use the INFO function to obtain portions of the results for use in your own customized reports or for further analysis.
Tip:
To performing more complex regression analysis use a forecasting context as discussed in "Forecasting Programs".REGRESS [NOINTERCEPT] dependent independent... [WEIGHTBY weight]
Directs Oracle OLAP to suppress the constant term (intercept) in the regression equation. The default is to calculate a constant term.
An expression to be used as the dependent variable in the regression.
In calculating the results, REGRESS loops over all the dimensions of the dependent and independent variables.
One or more expressions to be used as the independent variables (regressors) in the regression.
Specifies a weighted regression. The numeric expression weight supplies the weights for each data point (observation). Giving higher weights to more reliable observations results in a higher quality regression. WEIGHTBY must come last in the REGRESS command.
When weight is less than zero for any observation, an error occurs. When weight is equal to zero for any observation, that observation is ignored in the calculation. When WEIGHTBY is omitted, an unweighted regression is calculated.
In performing its calculations, the REGRESS command ignores any observation that has an NA
value.
The standard report for a regression shows the coefficient, standard error, and T-ratio for each independent variable; as well as the R-square, F-Statistic, number of observations, and standard error of estimate for the regression. To produce this report, type the following.
REGRESS.REPORT
For information on how to obtain portions of the results of REGRESS for your own reports or further analysis, use an INFO statement.
Example 10-92 Simple Regression
The following statements limit the product
dimension to Canoes
, then use regression to investigate the influence of advertising, price, and expense on the sales of canoes.
LIMIT product TO 'Canoes' REGRESS NOINTERCEPT sales advertising price expense
You can now execute REGRESS.REPORT as illustrated in Example 10-94, "Report for a Simple Regression" to see the results of the regression.
Example 10-93 Weighted Regression
The following statements use a weighted regression, in which districts are weighted using a variable called reliability
that has the following definition and values.
DEFINE reliability VARIABLE DECIMAL <district> DISTRICT RELIABILITY -------------- ----------- Boston 1.00 Atlanta 0.90 Chicago 1.00 Dallas 0.80 Denver 0.90 Seattle 0.60
The following statements perform the regression.
REGRESS NOINTERCEPT sales advertising price expense - WEIGHTBY reliability
You can now execute REGRESS.REPORT as illustrated in Example 10-94, "Report for a Simple Regression" to see the results of the regression.