Okay, suppose the viewing field is circular and we consider two particles as in the attached image.
Probability of being within the field: R0 > sqrt((x1+R1-x0)^2 + (y1+R1-y0)^2) Probability of being outside the field: R0 < sqrt((x2-R1-x0)^2 + (y2-R1-y0)^2) Since these are the limiting cases, it looks like the averaging I suggested will work. Jim On Thu, Feb 21, 2019 at 9:23 AM Rolf Turner <r.tur...@auckland.ac.nz> wrote: > > On 2/21/19 12:16 AM, PIKAL Petr wrote: > > Dear all > > > > Sorry, this is probably the most off-topic mail I have ever sent to > > this help list. However maybe somebody could point me to right > > direction or give some advice. > > > > In microscopy particle counting you have finite viewing field and > > some particles could be partly outside of this field. My > > problem/question is: > > > > Do bigger particles have also bigger probability that they will be > > partly outside this viewing field than smaller ones? > > > > Saying it differently, although there is equal count of bigger > > (white) and smaller (black) particles in enclosed picture (8), due to > > the fact that more bigger particles are on the edge I count more > > small particles (6) than big (4). > > > > Is it possible to evaluate this feature exactly i.e. calculate some > > bias towards smaller particles based on particle size distribution, > > mean particle size and/or image magnification? > > This is fundamentally a stereology problem (or so it seems to me) and as > such twists my head. Stereology is tricky and can be full of apparent > paradoxes. > > "Generally speaking" it surely must be the case that larger particles > have a larger probability of intersecting the complement of the window, > but to say something solid, some assumptions would have to be made. I'm > not sure what. > > To take a simple case: If the particles are discs whose centres are > uniformly distributed on the window W which is an (a x b) rectangle, > the probability that a particle, whose radius is R, intersects the > complement of W is > > 1 - (a-R)(b-R)/ab > > for R <= min{a,b}, and is 1 otherwise. I think! (I could be muddling > things up, as I so often do; check my reasoning.) > > This is an increasing function of R for R in [0,min{a,b}]. > > I hope this helps a bit. > > Should you wish to learn more about stereology, may I recommend: > > > @Book{baddvede05, > > author = {A. Baddeley and E.B. Vedel Jensen}, > > title = {Stereology for Statisticians}, > > publisher = {Chapman and Hall/CRC}, > > year = 2005, > > address = {Boca Raton}, > > note = {{ISBN} 1-58488-405-3} > > } > > cheers, > > Rolf > > -- > Honorary Research Fellow > Department of Statistics > University of Auckland > Phone: +64-9-373-7599 ext. 88276 > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code.
______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.