Re: st: RE: From: ipianah nic <ipianahnic@gmail.com>

[ipianah nic <ipianahnic@gmail.com>]

Nick,

my variables are genome and csf, and suppose I use glm/nl what will be
the model that i can use to extrapolate data so that i get predicted
values for where csf values are missing as below

genome	 csf
> 1	        2020
> 2	        1747
> 3	        1667
> 4	        1608
> 5	        1578
> 6	        1552
> 7	        1540
> 8	        1526
> 9	        1494
> 10	        1484
> 11	        1476
> 12	        1460
> 13	        1455
> 14	        1449
> 15	        1442
> 16	        1426
> 17	        1418
> 18	        1412
> 19	        1390
> 20	
> 21	
> 22	
> 23	
> 24	

Ipianah


On 2/11/11, Nick Cox <n.j.cox@durham.ac.uk> wrote:
> You decide whether it is more appropriate to use -nl-, -regress- after
> transformations, or -glm- with a log link. That's (at least) three to choose
> from. There is no answer free of assumptions about the most likely kind of
> error term.
>
> Also, if this is student homework, you got more help than you deserved. Real
> data that people care about don't arrive as Y and X.
>
> Nick
> n.j.cox@durham.ac.uk
>
> ipianah nic <ipianahnic@gmail.com>
>
> how do I fit an exponential regression curve and extrapolate the data
> using sample data below;
>
 genome	 csf
> 1	2020
> 2	1747
> 3	1667
> 4	1608
> 5	1578
> 6	1552
> 7	1540
> 8	1526
> 9	1494
> 10	1484
> 11	1476
> 12	1460
> 13	1455
> 14	1449
> 15	1442
> 16	1426
> 17	1418
> 18	1412
> 19	1390
> 20	1389
> 21	1384
> 22	1380
> 23	1380
> 24	1365
>
>
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