[R] conf. int. for lm() and Up-arrow

[Bill Venables]

> 
> Dear all,
> 
> Is there any function for calculating confidence limits 
> for coefficients in an lm() object? I know of the 
> confint() function in the MASS library working very 
> well on my binomial GLMs and I have tried it (using glm
> () , family=gaussian) but it gives NAs according to 
> below. Does the confint() function not accept gaussian 
> GLMs? Could there be convergence problems in the GLM? 
> Note the very low R2-value. Could the Hauck & Donner 
> phenomenon discussed in V & R (1999) occur in a 
> gaussian GLM?  I guess not and I have tried with 
> different epsilon but it does not change anything.

The software was never tested for this case as it seemed a little
pointless since the exact calculations can be done so simply.  (you
might like to do it as a homework exercise...)  I'll look at putting
in a switch to handle the case for future releases.

I suspect it will not work too well, though, as the method uses spline
interpolation to the signed square-root of the profile function, which
in this case is exactly linear.  I think cubic spline interpolation of
straight lines causes some numerical problems.  This is just a quick
response and you might like to check it.


> 
> I use R 1.1.0 on Windows 98.
> Sorry to bother you about this but earlier some R users 
> had problem using the Up arrow key to get the earlier 
> written text rows. I deleted those mails because I 
> usually use Windows NT. Now however I’m away from my 
> office using R on Windows 98 (something I didn\'t plan 
> to do). Could someone who have had this problem please 
> tell me how to do to be able to use the Up arrow key 
> again. 
> 
> Thanks for all hints!
> 
> 
> Sincerely,
> Tord Snäll
> 
> 
> 
> > glm.spe.var<- glm(OSPEABUN~ V1+V2+V3+V4+V5+V6+V7+V8, 
> family=gaussian, data=R)
> > lm.spe.var<- lm(OSPEABUN~V1+V2+V3+V4+V5+V6+V7+V8, 
> data=R)
> > summary(lm.spe.var)
> 
> 
> Residuals:
>       Min        1Q    Median        3Q       Max 
> -0.854243 -0.353655 -0.212623 -0.004446  2.729957 
> 
> Coefficients:
>              Estimate Std. Error t value Pr(>|t|)    
> (Intercept)  0.274985   0.028895   9.517  < 2e-16 ***
> V1           0.145041   0.041001   3.537 0.000445 ***
> V2          -0.002472   0.047220  -0.052 0.958276    
> V3          -0.016563   0.046899  -0.353 0.724120    
> V4          -0.065702   0.029530  -2.225 0.026573 *  
> V5           0.023614   0.031004   0.762 0.446665    
> V6           0.130698   0.031565   4.141 4.12e-05 ***
> V7          -0.009698   0.042213  -0.230 0.818398    
> V8          -0.041318   0.031670  -1.305 0.192672    
> ---
> Signif. codes:  0  `***\\\'  0.001  `**\\\'  0.01  `*\\\'  
> 0.05  
> `.\\\'  0.1  ` \\\'  1 
> 
> Residual standard error: 0.6257 on 460 degrees of 
> freedom
> Multiple R-Squared: 0.07881,    Adjusted R-squared: 
> 0.06279 
> F-statistic:  4.92 on 8 and 460 degrees of freedom,     
> p-value: 7.505e-006 
> 
> > summary(glm.spe.var)
> 
> 
> Deviance Residuals: 
>       Min         1Q     Median         3Q        Max  
> -0.854243  -0.353655  -0.212623  -0.004446   2.729957  
> 
> Coefficients:
>              Estimate Std. Error t value Pr(>|t|)    
> (Intercept)  0.274985   0.028895   9.517  < 2e-16 ***
> V1           0.145041   0.041001   3.537 0.000445 ***
> V2          -0.002472   0.047220  -0.052 0.958276    
> V3          -0.016563   0.046899  -0.353 0.724120    
> V4          -0.065702   0.029530  -2.225 0.026573 *  
> V5           0.023614   0.031004   0.762 0.446665    
> V6           0.130698   0.031565   4.141 4.12e-05 ***
> V7          -0.009698   0.042213  -0.230 0.818398    
> V8          -0.041318   0.031670  -1.305 0.192672    
> ---
> Signif. codes:  0  `***\\\'  0.001  `**\\\'  0.01  `*\\\'  
> 0.05  
> `.\\\'  0.1  ` \\\'  1 
> 
> (Dispersion parameter for gaussian family taken to be 
> 0.3915403)
> 
>     Null deviance: 195.52  on 468  degrees of freedom
> Residual deviance: 180.11  on 460  degrees of freedom
> AIC: 902.11
> 
> Number of Fisher Scoring iterations: 2
> 
> > confint(glm.spe.var, level=0.95)
> Waiting for profiling to be done...
>             2.5 % 97.5 %
> (Intercept)    NA     NA
> V1             NA     NA
> V2             NA     NA
> V3             NA     NA
> V4             NA     NA
> V5             NA     NA
> V6             NA     NA
> V7             NA     NA
> V8             NA     NA
> 
>  
> 
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-- 
Bill Venables,      Statistician,     CMIS Environmetrics Project
CSIRO Marine Labs, PO Box 120, Cleveland, Qld,  AUSTRALIA.   4163
Tel: +61 7 3826 7251           Email: Bill.Venables at cmis.csiro.au    
Fax: +61 7 3826 7304      http://www.cmis.csiro.au/bill.venables/



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