Re: st: exponential extrapolation

[Austin Nichols <austinnichols@gmail.com>]

ipianah nic <ipianahnic@gmail.com>:
One way to implement the bad idea:

clear
input genomes csf
genomes csf
1       2045
2       1793
3       1715
4       1665
5       1637
6       1613
7       1596
8       1579
9       1566
10      1554
11      1539
12      1527
13      1516
14      1511
15      1497
16      1486
17      1480
end
set obs 100
g lc=ln(csf)
replace gen=gen[_n-1]+1 if mi(gen)
ipolate lc gen, gen(ilc) e
g ic=exp(ilc)
sc ic c gen


On Tue, Mar 1, 2011 at 4:03 AM, Nick Cox <njcoxstata@gmail.com> wrote:
> In fact a look at the archives shows that you asked essentially the
> same question on 11 February, and unsurprisingly got a very similar
> answer from Maarten Buis and myself.
>
> So, what is going on? Perhaps you need to find someone in your
> institution who can talk you through these things.
>
> Incidentally, a plot of these data suggests to me that exponential
> decline is not the right model. There is curvature not taken out by
> looking at the data on log scale. Extrapolating the wrong model over
> more than 5 times the range of the observation strikes me as a bad
> idea, unless there is a compelling biological argument to the
> contrary.
>
> Nick
>
> On Tue, Mar 1, 2011 at 8:27 AM, Nick Cox <njcoxstata@gmail.com> wrote:
>> This looks more as if you have an exponential decline, not an
>> exponential distribution.
>>
>> As with your previous questions, fit an appropriate model using one or
>> more of -regress- after transformation, -glm- with log link, or -nl-.
>> Then use -predict-.
>>
>> Nick
>>
>> On Tue, Mar 1, 2011 at 7:00 AM, ipianah nic <ipianahnic@gmail.com> wrote:
>>
>>> my data set  exhibits an exponential distribution.how  can I
>>> extrapolate my data set as in the case below where i have genomes and
>>> csf..help please

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