Difference between revisions of "Manuals/calci/KFUNCTION"

From ZCubes Wiki
Jump to navigation Jump to search
(Created page with "kfun")
 
 
(4 intermediate revisions by 2 users not shown)
Line 1: Line 1:
kfun
+
<div style="font-size:30px">'''KFUNCTION (Number)'''</div><br/>
 +
*<math>Number</math> is any real number.
 +
 
 +
==Description==
 +
*This function shows the value of the K function.
 +
*In <math>KFUNCTION(Number)</math>,Number is any real number.
 +
*K function is named as Ripley's K Function.
 +
*It is defined as how the spatial clustering or dispersion of feature centroids changes when the neighborhood size changes.
 +
*When using this tool, specify the number of distances to evaluate and, optionally, a starting distance and/or distance increment. 
 +
*The K-Function is given as :
 +
<math>L(d)=\frac{\sqrt{A \sum_{i=1}^n \sum_{j=1,j\neq i}^n k(i,j)}}{\pi n(n-1)}</math>
 +
Where d is the distance, n is equal to the total number of features.
 +
*<math>A</math> represents the total area of the features and <math>k_{i,j}</math> is a weight.
 +
*If there is no edge correction, then the weight will be equal to one when the distance between i and j is less than d, and will equate to zero otherwise.
 +
 
 +
==Examples==
 +
# KFUNCTION(5) = 27648
 +
# KFUNCTION(15) = 1.8473984485535928e+99
 +
# KFUNCTION(6.453) = 86400000
 +
 
 +
==Related Videos==
 +
 
 +
{{#ev:youtube|v=Uz0MtFlLD-k|280|center|Relations and Functions}}
 +
 
 +
 
 +
==See Also==
 +
 
 +
*[[Manuals/calci/SUM | SUM]]
 +
*[[Manuals/calci/SQRT | SQRT]]
 +
 
 +
==References==
 +
[http://resources.esri.com/help/9.3/arcgisdesktop/com/gp_toolref/spatial_statistics_tools/how_multi_distance_spatial_cluster_analysis_colon_ripley_s_k_function_spatial_statistics_works.htm  K Function]
 +
 
 +
 
 +
 
 +
*[[Z_API_Functions | List of Main Z Functions]]
 +
 
 +
*[[ Z3 |  Z3 home ]]

Latest revision as of 17:16, 5 December 2018

KFUNCTION (Number)


  • is any real number.

Description

  • This function shows the value of the K function.
  • In ,Number is any real number.
  • K function is named as Ripley's K Function.
  • It is defined as how the spatial clustering or dispersion of feature centroids changes when the neighborhood size changes.
  • When using this tool, specify the number of distances to evaluate and, optionally, a starting distance and/or distance increment.
  • The K-Function is given as :

Where d is the distance, n is equal to the total number of features. 
  • represents the total area of the features and is a weight.
  • If there is no edge correction, then the weight will be equal to one when the distance between i and j is less than d, and will equate to zero otherwise.

Examples

  1. KFUNCTION(5) = 27648
  2. KFUNCTION(15) = 1.8473984485535928e+99
  3. KFUNCTION(6.453) = 86400000

Related Videos

Relations and Functions


See Also

References

K Function