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NAME
     ols - Estimate linear regressions.

SYNOPSIS
     ols [-_h] [-_p]  [-_r_a_w]  [-_l  labelstring]  [-_m  model_spec  ]
     [-_e_p_p] [_i_n_p_u_t_f_i_l_e_n_a_m_e]

DESCRIPTION
     _o_l_s takes a set of observations  from  the  specified  input
     file.  There must be exactly one observation per line. If no
     input file is specified, _o_l_s reads data from Standard Input.

     How is this input file organised?  All lines must  have  the
     same  layout  of  variables (fields), and the same number of
     variables.  Given a set of variables in a data file, you can
     run any regression which uses some (but not necessarily all)
     of these variables as l.h.s. or r.h.s. variable(s).

     Defining the layout of the input lines and  choosing  r.h.s.
     and  l.h.s.  variables  "by  hand" is slightly tedious.  _o_l_s
     offers a default behaviour which might be  useful.   In  the
     event  that  you  do  not choose l.h.s. and r.h.s. variables
     yourself, it assumes you want a regression as  follows:  the
     last  (rightmost)  variable on each line is considered to be
     the l.h.s.  variable and all other  variables  are  used  as
     r.h.s. regressors.

The Intercept
     _o_l_s knows nothing about  the  intercept  of  the  regression
     line.   By  default,  there is no intercept.  If you want an
     intercept, you must include a variable in the dataset  which
     always takes the value 1.0.  This is readily done using Unix
     tools like _a_w_k(1) or _s_e_d(1).

     Notice that  omitting  the  intercept  implies  _f_o_r_c_i_n_g  the
     regression  line  to  pass through the origin.  If this res-
     triction is forced unintentionally, it will almost certainly
     lead to nonsensical results.  Make sure you have a good rea-
     son for wanting to impose such a restriction, and  be  aware
     that  _o_l_s  will implicitly impose this restriction if you do
     not include a r.h.s. regressor which always takes the  value
     1.

OPTIONS
     -h   This option gives some minimal  quickstart  help.   All
          other arguments are ignored if it is found.

     -l labelstring
          This option allows you to attach variable names to your
          variables.  Thus, if you have three numbers per line in
          a regression of _y on _x with an intercept, you could use
          a labelstring of the form 'constant x y'.



Sun Release 4.1     Last change: 24 May 1991                    1






ols(Local)        MISC. REFERENCE MANUAL PAGES         ols(Local)



          The labels do several things.  They help in the  pretty
          printing of the regression results.  When the -p switch
          is used, the labels enable a  more  readable  generated
       


ols(Local)        MISC. REFERENCE MANUAL PAGES         ols(Local)



NAME
     ols - Estimate linear regressions.

SYNOPSIS
     ols [-_h] [-_p]  [-_r_a_w]  [-_l  labelstring]  [-_m  model_spec  ]
     [-_e_p_p] [_i_n_p_u_t_f_i_l_e_n_a_m_e]

DESCRIPTION
     _o_l_s takes a set of observations  from  the  specified  input
     file.  There must be exactly one observation per line. If no
     input file is specified, _o_l_s reads data from Standard Input.

     How is this input file organised?  All lines must  have  the
     same  layout  of  variables (fields), and the same number of
     variables.  Given a set of variables in a data 


ols(Local)        MISC. REFERENCE MANUAL PAGES         ols(Local)



NAME
     ols - Estimate linear regressions.

SYNOPSIS
     ols [-_h] [-_p]  [-_r_a_w]  [-_l  labelstring]  [-_m  model_spec  ]
     [-_e_p_p] [_i_n_p_u_t_f_i_l_e_n_a_m_e]

DESCRIPTION
     _o_l_s takes a set of observations  from  the  specified  input
     file.  There must be exactly one observation per line. If no
     input file is specified, _o_l_s reads data from Standard Input.

     How is this input file organised?  All lines must  have  the
     same  layout  of  variables (fields), and the same number of
     variables.  Given a set of variables in a data 


ols(Local)        MISC. REFERENCE MANUAL PAGES         ols(Local)



NAME
     ols - Estimate linear regressions.

SYNOPSIS
     ols [-_h] [-_p]  [-_r_a_w]  [-_l  labelstring]  [-_m  model_spec  ]
     [-_e_p_p] [_i_n_p_u_t_f_i_l_e_n_a_m_e]

DESCRIPTION
     _o_l_s takes a set of observations  from  the  specified  input
     file.  There must be exactly one observation per line. If no
     input file is specified, _o_l_s reads data from Standard Input.

     How is this input file organised?  All lines must  have  the
     same  layout  of  variables (fields), and the same number of
     variables.  Given a set of variables in a data