Difference between revisions of "Manuals/calci/KFUNCTION"

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<div style="font-size:30px">'''KFUNCTION (Number)'''</div><br/>
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*<math>Number</math> is any real number.
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==Description==
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*This function shows the value of the K function.
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*In <math>KFUNCTION(Number)</math>,Number is any real number.
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*K function is named as Ripley's K Function.
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*It is defined as how the spatial clustering or dispersion of feature centroids changes when the neighborhood size changes.
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*When using this tool, specify the number of distances to evaluate and, optionally, a starting distance and/or distance increment. 
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*The K-Function is given as :
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<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>
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Where d is the distance, n is equal to the total number of features.
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*<math>A</math> represents the total area of the features and <math>k_{i,j}</math> is a weight.
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*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.
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==Examples==
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# KFUNCTION(5) = 27648
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# KFUNCTION(15) = 1.8473984485535928e+99
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# KFUNCTION(6.453) = 86400000
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==Related Videos==
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{{#ev:youtube|v=Uz0MtFlLD-k|280|center|Relations and Functions}}
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==See Also==
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*[[Manuals/calci/SUM | SUM]]
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*[[Manuals/calci/SQRT | SQRT]]
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==References==
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[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]
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*[[Z_API_Functions | List of Main Z Functions]]
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*[[ Z3 |  Z3 home ]]

Latest revision as of 18:16, 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