[R] Trend value from smoothing spline trend fit

[Bert Gunter]

??

Change per year = (estimated end value - estimated begin value)/## years

Am I missing something subtle here?

Bert Gunter

"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )


On Tue, Aug 11, 2020 at 10:41 AM Dileepkumar R <dileepkunjaai using gmail.com>
wrote:

> Thank you for your reply.
>
> Yes, we can get the curve fit values on the line (as the length of input
> data frame) from predict.gam() function.  But I wish to get the trend value
> (in Trends in °C per decade or °C per year) as given in the Box 2.2, Table
> 1.  But I couldn't find any option in GAM method.
>
> Actually on of the reviewer of my paper suggested me to estimate the
> non-linear trend as given in this Box 2.2, Table 1 and Figure 1.
>
>
>
> Dileepkumar R
>
>
>
> On Tue, Aug 11, 2020 at 8:01 PM Bert Gunter <bgunter.4567 using gmail.com>
> wrote:
>
>> Caveat: Did not look at any of your links.
>>
>> However, the usual answer for this sort of question is ?predict.gam  (in
>> general, predict.whatevermethod)
>> Have you consulted the man page? If this is not what you want, you may
>> need to explain more carefully.
>>
>> Bert Gunter
>>
>> "The trouble with having an open mind is that people keep coming along
>> and sticking things into it."
>> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
>>
>>
>> On Tue, Aug 11, 2020 at 5:21 AM Dileepkumar R <dileepkunjaai using gmail.com>
>> wrote:
>>
>>> Dear All,
>>>
>>> I am trying to estimate the non -linear trend value from smooth spline
>>> trend fit (using the generalized additive model (GAM)).
>>>
>>> I want to estimate the trend value from a temperature dataset (spatial
>>> averaged annual meantime from 1906 to 2005) as given in the Box 2.2,
>>> Table
>>> 1  in the attached Google doc pdf.  (That pages are from  IPCC Assessment
>>> Report 5 chapter 2
>>> <
>>> https://www.ipcc.ch/site/assets/uploads/2017/09/WG1AR5_Chapter02_FINAL.pdf
>>> >,
>>> page number 21-22 )
>>>
>>> I do not understand how they estimate the single value trend with 95%
>>> confidence interval from a time-series data as given in the Box 2.2,
>>> Figure
>>> 1.  Is there any easy way to extract the trend value using mgcv library
>>> of
>>> R.?
>>>
>>> Google Doc Link:
>>>
>>> https://drive.google.com/file/d/1z3XLW-154dsZE6GrvQ4rH_fev9lqdsho/view?usp=sharing
>>>
>>> Thank you all in advance
>>>
>>> Dileepkumar R
>>>
>>>         [[alternative HTML version deleted]]
>>>
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>>

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