Hello, I am employing the Ripley's K function to evaluate my data and have some concerns regarding the maximum distance reported. My data was collected in 7 different sites. At each site we recorded the location x-y of the events. The 7 sites were had *"similar conditions" *but their extent vary, and in addition, not all sites presented the same number of events (number of events per site vary from 92 to up to 400 ). Each site was evaluated independently, meaning that Site-1 had their on set of events and own window of observation (W). I used the *ripras* function to define *W, *(for all sites, W is an irregular shaped window). I have run two first order exploratory tools (quadrat.test, clarkevans.test). The overall results is that my observations are not random and show aggregation tendencies for all sites. I applied the function* Kest* to all my seven sites to explore the second order properties, I did not provide a *r* value (as recommended in the help section) and here is the "curious" outcome. Indifferently of the area of W or the number of events per site, the maximum r-values reported for all sites is very similar (between 5000 m to 6140 m). I am trying to understand the reason behind these results. Is this an overall characteristic of my pattern OR is a result of the algorithm that spatstat employs to define r (e.g. it has a maximum threshold) Here my code: K2<-Kest(site2,correction="best"); where site2 is mydata max(K2$r) = 5,260 m Here the maximum distance values (in meters) for the other sites max(K1$r) = 6,140 max(K3$r) = 5,148 max(K4$r) = 5,016 max(K5$r) = 5,194 max(K6$r) = 5,055 max(K3$r) = 5,317 PS: I used the extent of the observation window for site 2 to create a random set of x-y locations (n=182, same than the observed number of events in this site). I run the test and the maximum distance was the same (5,260 m) I cannot find information how r is defined in the function Kest If any one any comment I will appreciate Thank you! Silvia Cordero-Sancho
Kest (spatstat) and "r" values
3 messages · Silvia Cordero-Sancho, Marcelino de la Cruz, Rolf Turner
Maybe the information related to r you are looking for is in the Warning section: "Warnings The estimator of K(r) is approximately unbiased for each fixed r. Bias increases with r and depends on the window geometry. For a rectangular window it is prudent to restrict the r values to a maximum of 1/4 of the smaller side length of the rectangle". Maybe I'm wrong but I think that Kest computest K(r) by default for r up to 1/4 of the shorter side of the *enclosing rectangle* of your window. HTH, Marcelino El 22/10/2014 a las 20:01, Silvia Cordero-Sancho escribi?:
Hello, I am employing the Ripley's K function to evaluate my data and have some concerns regarding the maximum distance reported. My data was collected in 7 different sites. At each site we recorded the location x-y of the events. The 7 sites were had *"similar conditions" *but their extent vary, and in addition, not all sites presented the same number of events (number of events per site vary from 92 to up to 400 ). Each site was evaluated independently, meaning that Site-1 had their on set of events and own window of observation (W). I used the *ripras* function to define *W, *(for all sites, W is an irregular shaped window). I have run two first order exploratory tools (quadrat.test, clarkevans.test). The overall results is that my observations are not random and show aggregation tendencies for all sites. I applied the function* Kest* to all my seven sites to explore the second order properties, I did not provide a *r* value (as recommended in the help section) and here is the "curious" outcome. Indifferently of the area of W or the number of events per site, the maximum r-values reported for all sites is very similar (between 5000 m to 6140 m). I am trying to understand the reason behind these results. Is this an overall characteristic of my pattern OR is a result of the algorithm that spatstat employs to define r (e.g. it has a maximum threshold) Here my code: K2<-Kest(site2,correction="best"); where site2 is mydata max(K2$r) = 5,260 m Here the maximum distance values (in meters) for the other sites max(K1$r) = 6,140 max(K3$r) = 5,148 max(K4$r) = 5,016 max(K5$r) = 5,194 max(K6$r) = 5,055 max(K3$r) = 5,317 PS: I used the extent of the observation window for site 2 to create a random set of x-y locations (n=182, same than the observed number of events in this site). I run the test and the maximum distance was the same (5,260 m) I cannot find information how r is defined in the function Kest If any one any comment I will appreciate Thank you! Silvia Cordero-Sancho [[alternative HTML version deleted]]
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On 23/10/14 08:59, Marcelino de la Cruz wrote:
Maybe the information related to r you are looking for is in the Warning section: "Warnings The estimator of K(r) is approximately unbiased for each fixed r. Bias increases with r and depends on the window geometry. For a rectangular window it is prudent to restrict the r values to a maximum of 1/4 of the smaller side length of the rectangle". Maybe I'm wrong but I think that Kest computest K(r) by default for r up to 1/4 of the shorter side of the *enclosing rectangle* of your window.
That is indeed correct, modulo a possible adjustment (which I believe rarely gets applied in practice) in terms of the estimated intensity of the process. See the code for rmax.rule() if you are interested in the details. cheers, Rolf
Rolf Turner Technical Editor ANZJS