Talk:Complete spatial randomness
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Expert tag
I have added this tag for two reasons. The context/assumptions are poorly defined ...is it being assumed that the distribution is spatially uniform as nothing here precludes non-uniform distributions (the actual contexts of the equations are poorly specified)? Secondly, if non-uniform distributions are excluded then various tests against a uniform or non-clustered non-hypothesis are available which could be linked or outlined. Melcombe (talk) 13:34, 1 June 2009 (UTC)
- The tag was removed after improving the question of whether non-uniform distributions were included. I have reapplied it, as the question of useful information about testing the "complete spatial randomness" model is still open. Melcombe (talk) 09:58, 4 June 2009 (UTC)
I agree.
A poorly written article. LoneRubberDragon (talk) 09:49, 26 February 2010 (UTC)
There is no reference to random numbers articles in end-references, such as the simplest of:
http://en.wikipedia.org/wiki/Statistical_randomness
And "spatial" randomness need not be added (with "spatial"), per se, in this manner, as it is not clear what you are referring to, other than random numbers on a sample space. And CLEARLY a random distribution (statistical randomness) system will produce a random space on sampling, in zero, one, two, through N dimensions. And "complete" is a dangerous word to use because complete is a mathematical word used of systems, and can easily be confused. Only a subset of people in science math lingustics would ever use that word this way only, without cross references. So complete spatial randomness sounds like a specific concept, that you end up not actually describing, because the language of science and math is very specific. I understand what you mean (and see the redundancy and incompleteness causing ineffectiveness of the article word use), exactly, but the layman reader will often be misled by such articles, best left as user talk pages. I may be the only reader who can read you and understand you, in this manner, because I AM also a linguist. LoneRubberDragon (talk) 09:49, 26 February 2010 (UTC)
The dangers of your article dialect reference:
http://en.wikipedia.org/wiki/Completeness
What you refer to specifically, as a possible synonymous industiral term, is already covered in Stationary Processes, and to some extent cover Wide Sense Stationary processes (WSS) process, also known as stationary processes, which both cover 1-D, 2-D, N-D processes. Wide Sense Stationary is implied by stationarity, where there's a mean, and the covariance of WSS is constant for a stationary sequence (Poisson PDF or otherwise), that is, the covariance or standard of deviation measure is also: shift invariant, that is linear space invairant, linear time invairant, or isotropic. You can show a distribution is stationary in covariance or shift-invairant, by showing that the correlation, that is specifically the autocorrelatiion function, is shift-invariant. This is shown by a finite bandwidth autocorrelation function that drops to zero as displacement increases beyond one sample, showing time invariance in no correlation over time (randomness), and a perfect correlation only at time=0, where the two correlate perfecty on only itself, aligned, for an infinite bandwidth random signal. However, it should be noted the converse of a shift-invariant autocorrelation does not Always Imply WSS in certain structured signals, but WSS are always shift invairiant autocorrelations, consider a degenerate delta function case where it has autocorrelation at t=0, and zero autocorrelation everywhere else, and yet it isn't random. Also, for band limited signals, the autocorrelation of a signal produces a sinc function related to the square window placed on the random signal spectrum, in fourier relationship, that is autocorrelation is 1 at t=0, and rapidly oscilates exponentially toward zero, as time shifts increase in the autocorrelation. They are technically not random signals, even if of white noise because the nest sample has some band limiting relationship to its nearest neighbors with a rapid decline with distance, leading to sudies of the autocorrelation Power Spectral Density. Anyway, this is (VERY BRIEFLY) a part of what makes a random system describable by mean and standard deviation, irrespective of the time or space of sampling. LoneRubberDragon (talk) 10:12, 26 February 2010 (UTC)
http://en.wikipedia.org/wiki/Wide_sense_stationary
http://en.wikipedia.org/wiki/Stationary_process
http://en.wikipedia.org/wiki/Covariance
http://en.wikipedia.org/wiki/Standard_deviation
http://en.wikipedia.org/wiki/Standard_error_(statistics)
http://en.wikipedia.org/wiki/Time_invariant_system
http://en.wikipedia.org/wiki/LTI_system_theory
http://en.wikipedia.org/wiki/Convergence_of_random_variables
http://en.wikipedia.org/wiki/Proofs_of_convergence_of_random_variables
http://en.wikipedia.org/wiki/Random_variable#Convergence
http://en.wikipedia.org/wiki/Correlation_function
http://en.wikipedia.org/wiki/Autocorrelation
http://en.wikipedia.org/wiki/Ergodic
http://en.wikipedia.org/wiki/Ensemble_average
http://en.wikipedia.org/wiki/Power_spectral_density
http://en.wikipedia.org/wiki/Fourier_transform#Uniform_continuity_and_the_Riemann.E2.80.93Lebesgue_lemma (Sinc and BW window)
But lacking cross references to standard terminology, to link your specific synonymous term, makes it difficult for layman to understand, for synonymous and standard terminology. This is pedagogically suspect. I understand exactly what you mean, but that is just myself, who is a well read "Dragon". Referenceless articles like this actually hurt my well-read eyes. That is why I refer to Microscan and Superresolution interchangeably in my comments on that article, so that the layman can see the university universe of related terms that may be in common use and less common use. LoneRubberDragon (talk) 10:12, 26 February 2010 (UTC)
Also, your bibliography article now doesn't download, when I tested it. LoneRubberDragon (talk) 10:21, 26 February 2010 (UTC)
http://www.dtic.mil/cgi-bin/GetTRDoc?AD=ADA291151&Location=U2&doc=GetTRDoc.pdf
And you should not mention Poisson distributions. Poisson distributions only happen is say quantized 2-D sampling of scalar fields, like in image procssing, as well as other physical quantized processes. However WSS and stationary processes can refer to uniform random distributions, Poisson random distributions, Gaussian random distributions, and any form of random distribution, that is in some sense stationary on 1 or more dimensions of sampling. Poisson distributions, I reiterate, apply specifically to systems like image processing, where pixel sampling of light intensity follows a Poisson distribution, which degenerates into a gaussian distribution, if the lambda increases beyond 5, and simplifies some math models by switching to Gaussian Approximations. But stationary processes can be with ANY Random Probability Density Function / random (PDF). LoneRubberDragon (talk) 10:40, 26 February 2010 (UTC)
http://en.wikipedia.org/wiki/Probability_density_function
http://en.wikipedia.org/wiki/Poisson_process
Remember, a uniform, gaussian, or any distribution PDF can be a stationary process if it satisfies randomness convergence, as a WSS system, with average and deviation / covariance measure sufficing for the sampling dimensions. LoneRubberDragon (talk) 10:50, 26 February 2010 (UTC)
This passage from Zen and the Art of Motorcycle Maintenance, Pirsig, relates my feelings here well. LoneRubberDragon (talk) 11:32, 26 February 2010 (UTC)
ZatAoMM, Prisig, 1974 (1982), pg. 264, "At present we're snowed under with an irrational expansion of blind data-gathering in the sciences because there's no rational format for any understanding of scientific creativity. At present we are snowed under with a lot of stylishness in the arts - thin art - because there's very little assimilation or extension into underlying form. We have artists with no scientific knowledge, and scientists with no artistic knowledge, and both are with not any spiritual sense of gravity at all. And the result is not just bad, it is ghastly. The time for real unification of technology and art is really long overdue."
http://en.wikipedia.org/wiki/Zen_and_the_Art_of_Motorcycle_Maintenance
This leads to a Tower of Babel. A tower of confusion, without any cross referencing, details, or art, as the metaphorical confusion arising from compartmentalization of cliques instead of cooperation of corporations (bodies of individuals as one body). LoneRubberDragon (talk) 11:32, 26 February 2010 (UTC)
http://en.wikipedia.org/wiki/Tower_of_babel
Sorry, again, if the comments section is longer than the article, as in Superresolution. These are hard subjects of sticky technicalities. LoneRubberDragon (talk)