pivot table procedure conceptually works

[pspp] / doc / regression.texi

diff --git a/doc/regression.texi b/doc/regression.texi
index e362c7fef139a3df806109729903a6c6437a5e61..9ff569d4d6bbc814c5d6abce895c14bc2f362901 100644 (file)
--- a/doc/regression.texi
+++ b/doc/regression.texi
@@ -45,7 +45,7 @@ linear model.
 REGRESSION
         /VARIABLES=@var{var_list}
         /DEPENDENT=@var{var_list}
-        /STATISTICS=@{ALL, DEFAULTS, R, COEFF, ANOVA, BCOV@}
+        /STATISTICS=@{ALL, DEFAULTS, R, COEFF, ANOVA, BCOV, CI[@var{conf}]@}
         /SAVE=@{PRED, RESID@}
 @end display
 
@@ -61,9 +61,10 @@ are treated as explanatory variables in the linear model.
 
 All other subcommands are optional:
 
-The @subcmd{STATISTICS} subcommand specifies the statistics to be displayed:
+The @subcmd{STATISTICS} subcommand specifies additional statistics to be displayed.
+The following keywords are accepted:
 
-@table @code
+@table @subcmd
 @item ALL
 All of the statistics below.
 @item R
@@ -71,19 +72,29 @@ The ratio of the sums of squares due to the model to the total sums of
 squares for the dependent variable.
 @item COEFF
 A table containing the estimated model coefficients and their standard errors.
+@item CI (@var{conf})
+This item is only relevant if COEFF has also been selected.  It specifies that the
+confidence interval for the coefficients should be printed.  The optional value @var{conf},
+which must be in parentheses, is the desired confidence level expressed as a percentage.
 @item ANOVA
 Analysis of variance table for the model.
 @item BCOV
 The covariance matrix for the estimated model coefficients.
+@item DEFAULT
+The same as if R, COEFF, and ANOVA had been selected.
 @end table
 
 The @subcmd{SAVE} subcommand causes @pspp{} to save the residuals or predicted
 values from the fitted
 model to the active dataset. @pspp{} will store the residuals in a variable
-called RES1 if no such variable exists, RES2 if RES1 already exists,
-RES3 if RES1 and RES2 already exist, etc. It will choose the name of
-the variable for the predicted values similarly, but with PRED as a
+called @samp{RES1} if no such variable exists, @samp{RES2} if @samp{RES1} 
+already exists,
+@samp{RES3} if @samp{RES1} and @samp{RES2} already exist, etc. It will
+choose the name of
+the variable for the predicted values similarly, but with @samp{PRED} as a
 prefix.
+When @subcmd{SAVE} is used, @pspp{} ignores @cmd{TEMPORARY}, treating
+temporary transformations as permanent.
 
 @node Examples
 @subsection Examples