hi
On Mon, 30 Aug 2004, Boud Roukema wrote:
hi,
On Mon, 30 Aug 2004, Bartosz Lew wrote:
witam
On Fri, 27 Aug 2004, Boud Roukema wrote:
-> on month scale changes very rapidly - some blobs just stop for some time, and then start up again.
plus it often happens that they fade away very quickly or change shape so within a few months the recognition of the same blob mae sometimes be difficult.
OK, but these don't seem to affect the statistics as far as i understand.
sure - it's just a problem with measurments.
It seems to me that blobs that fade are no longer detected, hence no longer relevant; and if a blob changes shape without changing speed, then it does increase the error bar (determining the centre is difficult), or drop out from detection statistics.
sure - I agree. but if the blob fades out the whole sequence of previous observations might be useless resulting in having one source less in the sample.
My initial reaction is that in a statistical sample these should average out, provided that the errors are random and symmetrically distributed.
Alternatively: can we try to statistically correct for this?
Given that blobs stop and then start again, or change direction, but are only *detected* when they are moving superluminally, then it would seem to me that the true average speed is slower than estimated from the doppler factor.
hmm this I quite don't understand ? why do you say so, that they are only detected when they are superliuminal. in fact superluminality isn't a condition "sine qua non" for doing this thing.
It seems to me that they are more *likely* to be detected when they are superluminal - and the doppler boosting has a big role in this.
I agree, thats why we try to play only with these guys, but it's a trade of choosing between luminosity (superliminality) and angular resolution ofthe VLBI capabilities measuring proper motions.
Most practical cosmology is about statistical corrections - it requires careful modelling and correct statistical analysis, but it can be done.
Is it reasonable to use the observational data which *shows* the erratic behaviour of these objects to statistically model this?
If yes, then we would have the necessary correction factor.
from what I've done and played with the real data, I see that the final value is quite sinsitive on precise measurments from the maps !! so true - the big sample is needed and this should work.
:)
pozdr boud
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