X-Git-Url: https://pintos-os.org/cgi-bin/gitweb.cgi?a=blobdiff_plain;f=doc%2Fregression.texi;h=d3d5a198f79cd92d80dc09d1a4d69e7cb7f4bf50;hb=refs%2Fheads%2Fctables10;hp=127ec7164567bce7b2f2d2b6233d5e97ca526c03;hpb=e8b26fb0d765310d4c7400c39465008f1bb8601d;p=pspp

diff --git a/doc/regression.texi b/doc/regression.texi
index 127ec71645..d3d5a198f7 100644
--- a/doc/regression.texi
+++ b/doc/regression.texi
@@ -1,3 +1,12 @@
+@c PSPP - a program for statistical analysis.
+@c Copyright (C) 2017, 2020 Free Software Foundation, Inc.
+@c Permission is granted to copy, distribute and/or modify this document
+@c under the terms of the GNU Free Documentation License, Version 1.3
+@c or any later version published by the Free Software Foundation;
+@c with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts.
+@c A copy of the license is included in the section entitled "GNU
+@c Free Documentation License".
+@c
 @node REGRESSION
 @section REGRESSION
 
@@ -15,12 +24,12 @@ Let @math{X_{11}, X_{12}}, @dots{}, @math{X_{1n}} denote the @math{n} observatio
 of the first explanatory variable;
 @math{X_{21}},@dots{},@math{X_{2n}} denote the @math{n} observations of the second
 explanatory variable;
-@math{X_{k1}},@dots{},@math{X_{kn}} denote the @math{n} observations of 
+@math{X_{k1}},@dots{},@math{X_{kn}} denote the @math{n} observations of
 the @math{k}th explanatory variable.
 
-@item The dependent variable @math{Y} has the following relationship to the 
+@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.
@@ -30,7 +39,7 @@ This relationship is called the @dfn{linear model}.
 
 The @cmd{REGRESSION} procedure estimates the coefficients
 @math{b_0,@dots{},b_k} and produces output relevant to inferences for the
-linear model. 
+linear model.
 
 @menu
 * Syntax::                      Syntax definition.
@@ -45,7 +54,8 @@ 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}, TOL]@}
+        @{ /ORIGIN | /NOORIGIN @}
         /SAVE=@{PRED, RESID@}
 @end display
 
@@ -61,7 +71,8 @@ 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 which statistics are to be displayed.
+The following keywords are accepted:
 
 @table @subcmd
 @item ALL
@@ -71,21 +82,40 @@ 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 TOL
+The variance inflation factor and its reciprocal.  This has no effect unless COEFF is also given.
+@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
-called @samp{RES1} if no such variable exists, @samp{RES2} if @samp{RES1} 
+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
@@ -108,6 +138,6 @@ a  8.838262 -29.25689
 b  6.200189 -18.58219
 end data.
 list.
-regression /variables=v0 v1 v2 /statistics defaults /dependent=v2 
+regression /variables=v0 v1 v2 /statistics defaults /dependent=v2
            /save pred resid /method=enter.
 @end example