REGRESSION: Implement /ORIGIN subcommand.

[pspp] / doc / regression.texi

diff --git a/doc/regression.texi b/doc/regression.texi
index 9ff569d4d6bbc814c5d6abce895c14bc2f362901..9a159014d005b3d1900645dfff0ef85bd783027f 100644 (file)
--- a/doc/regression.texi
+++ b/doc/regression.texi
@@ -20,7 +20,7 @@ the @math{k}th explanatory variable.
 
 @item The dependent variable @math{Y} has the following relationship to the 
 explanatory variables:
-@math{Y_i = b_0 + b_1 X_{1i} + ... + b_k X_{ki} + Z_i} 
+@math{Y_i = b_0 + b_1 X_{1i} + ... + b_k X_{ki} + Z_i}
 where @math{b_0, b_1, @dots{}, b_k} are unknown
 coefficients, and @math{Z_1,@dots{},Z_n} are independent, normally
 distributed @dfn{noise} terms with mean zero and common variance.
@@ -46,6 +46,7 @@ REGRESSION
         /VARIABLES=@var{var_list}
         /DEPENDENT=@var{var_list}
         /STATISTICS=@{ALL, DEFAULTS, R, COEFF, ANOVA, BCOV, CI[@var{conf}]@}
+        @{ /ORIGIN | /NOORIGIN @}
         /SAVE=@{PRED, RESID@}
 @end display
 
@@ -61,7 +62,7 @@ are treated as explanatory variables in the linear model.
 
 All other subcommands are optional:
 
-The @subcmd{STATISTICS} subcommand specifies additional statistics to be displayed.
+The @subcmd{STATISTICS} subcommand specifies which statistics are to be displayed.
 The following keywords are accepted:
 
 @table @subcmd
@@ -82,8 +83,17 @@ Analysis of variance table for the model.
 The covariance matrix for the estimated model coefficients.
 @item DEFAULT
 The same as if R, COEFF, and ANOVA had been selected.
+This is what you get if the /STATISTICS command is not specified,
+or if it is specified without any parameters.
 @end table
 
+The @subcmd{ORIGIN} and @subcmd{NOORIGIN} subcommands are mutually
+exclusive.  @subcmd{ORIGIN} indicates that the regression should be
+performed through the origin.  You should use this option if, and
+only if you have reason to believe that the regression does indeed
+pass through the origin --- that is to say, the value @math{b_0} above,
+is zero.  The default is @subcmd{NOORIGIN}.
+
 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