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Running /home/krg/bin/profile.do ...
Compile number 170082

. do boxbod.do 

. /* NIST/ITL StRD
> Dataset Name:  BoxBOD            (BoxBOD.dat)
> 
> File Format:   ASCII
>                Starting Values   (lines 41 to 42)
>                Certified Values  (lines 41 to 47)
>                Data              (lines 61 to 66)
> 
> Procedure:     Nonlinear Least Squares Regression
> 
> Description:   These data are described in detail in Box, Hunter and
>                Hunter (1978).  The response variable is biochemical
>                oxygen demand (BOD) in mg/l, and the predictor
>                variable is incubation time in days.
> 
> 
> Reference:     Box, G. P., W. G. Hunter, and J. S. Hunter (1978).
>                Statistics for Experimenters.  
>                New York, NY: Wiley, pp. 483-487.
> 
> 
> 
> 
> 
> Data:          1 Response  (y = biochemical oxygen demand)
>                1 Predictor (x = incubation time)
>                6 Observations
>                Higher Level of Difficulty
>                Observed Data
> 
> Model:         Exponential Class
>                2 Parameters (b1 and b2)
> 
>                y = b1*(1-exp[-b2*x])  +  e
> 
> 
>  
>           Starting values                  Certified Values
> 
>         Start 1     Start 2           Parameter     Standard Deviation
>   b1 =   1           100           2.1380940889E+02  1.2354515176E+01
>   b2 =   1             0.75        5.4723748542E-01  1.0455993237E-01
> 
> Residual Sum of Squares:                    1.1680088766E+03
> Residual Standard Deviation:                1.7088072423E+01
> Degrees of Freedom:                                4
> Number of Observations:                            6  
> */
. 
. clear

. 
. scalar N         = 6  

. scalar df_r      = 4

. scalar df_m      = 2

. 
. scalar rss       = 1.1680088766E+03

. scalar rmse      = 1.7088072423E+01

. 
. scalar b1        = 2.1380940889E+02  

. scalar seb1      = 1.2354515176E+01

. scalar b2        = 5.4723748542E-01  

. scalar seb2      = 1.0455993237E-01

. 
. qui input double(y x)

. 
. nl ( y = {b1}*(1-exp(-{b2}*x)) ), init(b1 1 b2 1) eps(1e-10)
(obs = 6)

Iteration 0:  residual SS =    184700
Iteration 1:  residual SS =  13388.66
Iteration 2:  residual SS =   7327.64
Iteration 3:  residual SS =  2375.331
Iteration 4:  residual SS =  1388.389
Iteration 5:  residual SS =   1168.01
Iteration 6:  residual SS =  1168.009
Iteration 7:  residual SS =  1168.009
Iteration 8:  residual SS =  1168.009
Iteration 9:  residual SS =  1168.009
Iteration 10:  residual SS =  1168.009
Iteration 11:  residual SS =  1168.009
Iteration 12:  residual SS =  1168.009
Iteration 13:  residual SS =  1168.009
Iteration 14:  residual SS =  1168.009
Iteration 15:  residual SS =  1168.009


      Source |      SS            df       MS
-------------+----------------------------------    Number of obs =          6
       Model |  187140.99          2  93570.4956    R-squared     =     0.9938
    Residual |  1168.0089          4  292.002219    Adj R-squared =     0.9907
-------------+----------------------------------    Root MSE      =   17.08807
       Total |     188309          6  31384.8333    Res. dev.     =   48.65504

------------------------------------------------------------------------------
           y | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         /b1 |   213.8094   12.35451    17.31   0.000     179.5078     248.111
         /b2 |   .5472375     .10456     5.23   0.006     .2569325    .8375425
------------------------------------------------------------------------------

. 
. assert N    == e(N)

. assert df_r == e(df_r)

. assert df_m == e(df_m)

. 
. lrecomp [b1]_b[_cons] b1 [b2]_b[_cons] b2 () /*
> */ [b1]_se[_cons] seb1 [b2]_se[_cons] seb2 () /*
> */ e(rmse) rmse e(rss) rss

[b1]_b[_cons]        7.9
[b2]_b[_cons]        7.3
-------------------------
min                  7.3

[b1]_se[_cons]       6.8
[b2]_se[_cons]       6.7
-------------------------
min                  6.7

e(rmse)             11.1
e(rss)              10.4

. 
. 
end of do-file