Thanks for your support Younges my idea was inspired and adapted from the Kendall correlation coefficient (http://en.wikipedia.org/wiki/Kendall_tau_rank_correlation_coefficient ) but with the pb of cardinality.
- number of concordances (accurate observations) - number of discordances(omission + false positive) and do a sum and then a normalisation to get something like 1.0 = max corcordance max 0.0 = max discordance. but I am not sure how to normalize: - the range of concordance [0, Card(A)] is smaller than the discordance [0, Card(A+B)] so anormalisation should be something like (2Card(A)+Card(B)) but I am not sure about that , and I am not sure the whole idea is right.. How did you normalize in your calcul? On Wed, Mar 2, 2011 at 5:50 AM, Younes Fadakar <yfa.st...@ymail.com> wrote: > Dear Nicolas, > > This is not the answer to your question but a try to implement your idea and > to have an experience with it. > Please see the attached, the output. > It seems the total score provided by the method is very dependent to the > 'r', the radius of search for neighbors around each ref point (A). > However, being able to define the right 'r', the score seems a realistic > measure of accuracy to me. > Of course, this is just a practical understanding hoping the community could > provide the statistical references. > Anyway, I liked the idea. > > Best Regards, > . > Younes > yfa.st...@ymail.com > http://alghalandis.com > ________________________________ > > > ________________________________ > From: Nicolas Maisonneuve <n.maisonne...@gmail.com> > To: ai-geostats@jrc.it > Sent: Mon, 28 February, 2011 6:21:49 PM > Subject: AI-GEOSTATS: Estimation of the position accuracy of 2 set of points > with different cardinalities > > Hi everyone, > > A simple question: > I have 1 set of 2D location points A that I use as reference. > I have another set of location points B generated by observations. > > Is there any standard method/measure to estimate a kind of position > accuracy error knowing that > - A and B dont have the same cardinality of elements e.g. B could have > more points than A? > - a point in A should be associated to only one point in B. > > For the moment I created my own error measure using 3 estimations. > for a given accuracy rate (<20 meters) I compute: > - O: number of omissions (when there is no observation in B closed > enough of a point in A) , > - FP: number of false positive (when a B point has been observed but > not closed to a A point - or already taken from another > observation) > - M: number of matching (when a B point is closed enought of a A point) > and then I aggregate the result = M- (O+FP) to get an indicator.. > > I am pretty sure there are other more traditional ways to do that. > > Thanks in advance > -NM > + > + To post a message to the list, send it to ai-geost...@jrc.ec.europa.eu > + To unsubscribe, send email to majordomo@ jrc.ec.europa.eu with no subject > and "unsubscribe ai-geostats" in the message body. DO NOT SEND > Subscribe/Unsubscribe requests to the list > + As a general service to list users, please remember to post a summary of > any useful responses to your questions. > + Support to the forum can be found at http://www.ai-geostats.org/ > > + + To post a message to the list, send it to ai-geost...@jrc.ec.europa.eu + To unsubscribe, send email to majordomo@ jrc.ec.europa.eu with no subject and "unsubscribe ai-geostats" in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list + As a general service to list users, please remember to post a summary of any useful responses to your questions. + Support to the forum can be found at http://www.ai-geostats.org/
