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Last seen: Jul 13, 2026
@jamespa — thanks. No rush, I posted a bit too hastily earlier and need to correct the plot once I realised it was not correct! This may also be a r...
I can get both the fitted values, which are row specific ie depend on the OAT (ambient) value for that row, so in effect they are random, or the regre...
Short of watermarking every post and every chart with 'N=1' there isn't much more I can do than I already have done, point out regularly that this is ...
Nonetheless, useful commentary in that it tells us 'smart' meters are not so much about letting consumers know much about their consumption — wasn't t...
@transparent may have something useful to add here, he knows a lot about smart meters. My initial thought is do you actually need this level of ...
@ian33a — I have a sort of residual interest in this problem as I used to have an oil tank (and boiler) and I remember how vague my usage measurements...
I agree, and that is in effect what @jamespa and I have been doing! That's for the link and it seems I have been teaching grandmothers to suck eg...
@ian33a — a measured heat loss always trumps a calculated (whatiffery spreadsheet) heat loss, providing certain requirements are met. Firstly, the I...
Yes, see below. They are just standard regression lines, just as in any spreadsheet, but in R you have more control and more options, but as I have sa...
Using past oil usage to estimate heat loss is tricky. Firstly it is very unusual to have accurate interval usage. You fills your tank and runs your ...
@jamespa — this version may be marginally better:
@jamespa — the 0900 2100 IAT/OAT data is now in R and as a starter for ten I have distinguished between setback and setback and hour, 0900 and 2100, b...
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