[R-sig-ME] modelling seasonal patterns as random effects in a monthly time series

Chris Howden chris at trickysolutions.com.au
Thu Feb 16 00:16:07 CET 2012


Very Sorry everyone for the redundant reply to jianyun.

for some reason I thought that came from the r-sig-Eco list I'm on and
I also managed to not process  jianyun's last sentence.

I think I must still be half asleep, my only excuse is that I haven't
had my cup of tea yet.

Chris Howden
Founding Partner
Tricky Solutions
Tricky Solutions 4 Tricky Problems
Evidence Based Strategic Development, IP Commercialisation and
Innovation, Data Analysis, Modelling and Training

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On 16/02/2012, at 10:09, Chris Howden <chris at trickysolutions.com.au> wrote:

> Try lme and lme4. There is also a list calle r-sig-me.
>
>
>
> Chris Howden
> Founding Partner
> Tricky Solutions
> Tricky Solutions 4 Tricky Problems
> Evidence Based Strategic Development, IP Commercialisation and
> Innovation, Data Analysis, Modelling and Training
>
> (mobile) 0410 689 945
> (fax / office)
> chris at trickysolutions.com.au
>
> Disclaimer: The information in this email and any attachments to it are
> confidential and may contain legally privileged information. If you are not
> the named or intended recipient, please delete this communication and
> contact us immediately. Please note you are not authorised to copy,
> use or disclose this communication or any attachments without our
> consent. Although this email has been checked by anti-virus software,
> there is a risk that email messages may be corrupted or infected by
> viruses or other
> interferences. No responsibility is accepted for such interference. Unless
> expressly stated, the views of the writer are not those of the
> company. Tricky Solutions always does our best to provide accurate
> forecasts and analyses based on the data supplied, however it is
> possible that some important predictors were not included in the data
> sent to us. Information provided by us should not be solely relied
> upon when making decisions and clients should use their own judgement.
>
> On 16/02/2012, at 8:35, Jianyun Wu <jianyun.fred.wu at gmail.com> wrote:
>
>> Hi Ken,
>> I have a monthly time series, and the seasonal pattern is obvious where
>> peaks are in Dec and drops in Jan. However due to various "external"
>> factors, the seasonal variation during the year may change from time to
>> time. The traditional practice here is to use seasonal dummies to treat
>> them deterministically.
>> Therefore I am curious that instead of treating them as fixed effects,
>> whether random effects model can apply for 12 month in each year.
>> We do not use Box-Jenkin approach to difference the time series as we can
>> hardly find a significant association on a variable of interest. But using
>> determinstic trend and seasonal dummies do....
>> Thanks
>> Fred
>>
>> On Thu, Feb 16, 2012 at 8:12 AM, Kenneth Frost <kfrost at wisc.edu> wrote:
>>
>>> Hi, Fred-
>>>
>>> The answer to your question is probably yes, but you need to provide more
>>> details about what you want to do.
>>>
>>> Ken
>>>
>>> On 02/15/12, Jianyun Wu   wrote:
>>>> Dear All,
>>>>
>>>> Is there any function or packages in R that I can treat seasonal patterns
>>>> as random effects in a monthly time series?
>>>>
>>>> Is this possible to formulate such a model using nlme, lme4 or other
>>>> available mixed model packages?
>>>>
>>>> Thanks and Regards
>>>>
>>>> Fred
>>>>
>>>>    [[alternative HTML version deleted]]
>>>>
>>>> _______________________________________________
>>>> R-sig-mixed-models at r-project.org mailing list
>>>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>>>
>>>
>>
>>  [[alternative HTML version deleted]]
>>
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