Distance-Based Weights

Distance-based weights are constructed using distance measures between all pairs of observations. The neighbor relation can be determined by a given distance band, so every other observation that falls within the distance band is considered as neighbors of one observation. Another way to determine neighbor relation is to find K nearest neighbors (KNN) for each observation.

For more information, please read: https://geodacenter.github.io/workbook/4b_dist_weights/lab4b.html

1. getMinDistancethreshold()

In order to avoid isolates (islands) that would result from too stringent a critical distance, the distance must be chosen such that each location has at least one neighbor. Such a distance conforms to a max-min criterion, i.e., it is the largest of the nearest neighbor distances.

function getMinDistancethreshold(String mapUid, Boolean isArc, Boolean isMile)

Arguments

Input Arguments	Type	Description
mapUid	String	the unique map id
isArc	boolean	if compute arc distance between two observations. Default: FALSE.
isMile	boolean	if convert distance unit from mile to kilometer(KM). Default: TRUE.

Return

Value	Description
Number	the minimum distance that makes sure each observation has at least one neighbor

2. getDistanceWeights()

With the distance band, one can create a distance-based spatial weights using WINDOW function distance_weights()

Short version:

function getDistanceWeights(String mapUid, Number distBand,
    Number power, 
    Boolean isInverse, 
    Boolean isArc,
    Boolean isMile)

Arguments:

Input Arguments	Type	Description
map_uid	String	the unique map id
distBand	Number	the distance band/threshold that makes sure each observation has at least one neighbor
power	Number	the power/exponent corresponds to the number of times the base (dist_band) is used as a factor. Default: 1.
isInverse	Boolean	if apply inverse on distance value. Default: False.
isArc	Boolean	if compute arc distance between two observations. Default: FALSE.
isMile	Boolean	if convert distance unit from mile to kilometer(KM). Default: TRUE.

Return

Value	Description
WeightsResult	the weights structure for each observation.

3. getKnnWeights()

function getKnnWeights(String mapUid, Number k,
    Number power, 
    Boolean isInverse, 
    Boolean isArc,
    Boolean isMile)

Arguments:

Input Arguments	Type	Description
mapUid	String	the unique map id
k	Number	the k nearest neighbors
power	Number	the power/exponent corresponds to the number of times the base (dist_band) is used as a factor. Default: 1.
isInverse	Boolean	if apply inverse on distance value. Default: False.
isArc	Boolean	if compute arc distance between two observations. Default: FALSE.
isMile	Boolean	if convert distance unit from mile to kilometer(KM). Default: TRUE.

Return

Value	Description
WeightsResult	the weights structure for each observation.

Try it yourself in the playground (jsgeoda + deck.gl):