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"Nick" <tulse04-news1@xxxxxxxxxxx> wrote in message
news:2eadnW5llPBtmAXYRVnyjQA@xxxxxxxxx
>
>
> <iwan2no@xxxxxxxxxxx> wrote in message
> news:1167589111.940345.138320@xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
>> Hi,
>>
>> I've got a simple question about predicting temperature readings. I got
>> a couple of responses yesterday... but I'm still not too clear about a
>> few things...
>>
>> Say I record temperature readings of a place every minute. I do this
>> for 10 minutes, i.e. I've got 10 readings (T1 to T10). I then make a
>> prediction of the temperature for the 11th minute, P11. I then get a
>> reading for the 11th minute as well, T11.
>>
>> Now in the 12th minute, I make my prediction (P12) based on *only* the
>> past 10 temperature readings, i.e. T2 to T11.
>>
>> So basically, every prediction can ONLY be made based on the last 10
>> readings.
>>
>> In addition, I also need to state the accuracy of the predicted
>> reading, e.g. there is a 95% chance that the predicted temperature at
>> the 12th minute, i.e. P12, is within +/-0.5C.
>>
>> Another important point is that I need to use a technique that is VERY
>> computationally simple. So I definitely don't want to deal with complex
>> computations. In fact, I'd prefer a simple method, even if that means
>> giving up some accuracy.
>>
>> Now it seems to me that there could be two ways of doing this:
>>
>> 1. Using Time Series Forecasting
>> 2. Using Linear Regression
>>
>> Let me first state some things about Time Series Forecasting:
>> =============================================
>> Since I'm only considering a very small time frame, there won't be any
>> seasonal components. Only a trend. I guess I can use something like
>> AR(4) (i.e. p=4) for example. I make the assumption that q=0. But then
>> I understand that I need to compute some coefficients, and the way to
>> do that could be using say the durbin-levinson algorithm. Am I right in
>> saying this? It seems to me that it's computationally quite difficult?
>> I can't really find any examples of this using actual numbers, e.g.:
>> 20,21,20.5,22.4,23.8, 24.6,26,27.3,27.9,28.5,29.....what next? what are
>> the precise steps?
>>
>> Now for Linear Regression
>> ===================
>> I could do a simple linear regression and use that to make the
>> predictions. Also, since the trend of the temperature may change
>> suddenly, I'm thinking of using weights, so that more recent
>> temperature readings have a greater impact on the line of best fit. By
>> the way, I plan to use the least squares method to work out the model.
>>
>> Questions:
>> ========
>> 1. Why is it I can't find any examples where linear regression is used
>> to make predictions where time is the factor used to make the
>> prediction of the measured variable? All the examples seem to be say
>> between two measured parameters, e.g. temperature and humidity. Is it
>> wrong to use linear regression?
>>
>> 2. Can I add weights to the AR model to give priority to more recent
>> readings? Couldn't seem to find any info on that in the book I'm
>> referring to. Or are the coefficients the weights?
>>
>> 3. What's the main difference between Linear Regression (LR) and Time
>> Series Forecasting (TSF)? How do I know when to use LR and when to use
>> TSF? Can't find any info on this anywhere...
>>
>
> Your question seems a no-brainer.
>
> After all, whatever you call it your series is a time series because it
> relates to time.
>
> From memory (30 years ago) and searching on Google, much of time-series
> forecasting uses linear regression. I think that greater dependence is
> based on the most recent readings than earlier ones - possibly
> autocorrelation.
>
> See
> http://socserv.mcmaster.ca/jfox/Books/Companion/appendix-timeseries-regression.pdf
>
> Chris Chatfield was an author that is very good on time-series - indeed, I
> attended a seminar given by him when I was at university.
I would like to know why you have started a new thread on this topic as I
have now discovered you have asked a question on the same subject 18 hours
ago.
I don't see why you didn't ask them rather than discontinue that thread and
effectively throw away their responses and start again.
IMHO such behaviour is not in line with etiquette.
Nick
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