FLQ: Focal Location Quotient

In lctools: Local Correlation, Spatial Inequalities, Geographically Weighted Regression and Other Tools

Description

This is the implementation of the Focal Location Quotients proposed by Cromley and Hanink (2012). The function calculates the standard LQ and the Focal LQ based on a kernel of nearest neighbours. Two weighted schemes are currently supported: binary and bi-square weights for a fixed number of nearest neighbours set by the user.

Usage

FLQ(Coords, Bandwidth, e, E, Denominator, WType = "Bi-square")

Arguments

Coords	a numeric matrix or vector or dataframe of two columns giving the X,Y coordinates of the observations (data points or geometric / population weighted centroids)
Bandwidth	a positive value that defines the number of nearest neighbours for the calculation of the weights
e	a numeric vector of a variable e_i as in the nominator of the Equation 1 (Cromley and Hanink, 2012) referring to the employment in a given sector for each location
E	a numeric vector of a variable E_i as in the nominator of the Equation 1 (Cromley and Hanink, 2012) referring to the total employment in a given sector for each location
Denominator	a ratio as in the denominator (e/E) of the Equation 1 (Cromley and Hanink, 2012), where e and E are total employment in the given sector and overall employment in the reference economy, respectively.
WType	string giving the weighting scheme used to compute the weights matrix. Options are: "Binary", "Bi-square". Default is "Bi-square". Binary: weight = 1 for distances less than or equal to the distance of the furthest neighbour (H), 0 otherwise; Bi-square: weight = (1-(ndist/H)^2)^2 for distances less than or equal to H, 0 otherwise

Value

FLQ returns a list of 2 vectors:

LQ	A numeric vector with the Location Quotient values
FLQ	A numeric vector with the Focal Location Quotient values

Author(s)

Stamatis Kalogirou <[e-mail]>

References

Cromley, R. G. and Hanink, D. M. (2012), Focal Location Quotients: Specification and Application, Geographical Analysis, 44 (4), pp. 398-410. doi: 10.1111/j.1538-4632.2012.00852.x

Kalogirou, S. (2015) Spatial Analysis: Methodology and Applications with R. [ebook] Athens: Hellenic Academic Libraries Link. ISBN: 978-960-603-285-1 (in Greek). https://repository.kallipos.gr/handle/11419/5029?locale=en

Examples

data(VotesGR)
res<-FLQ(cbind(VotesGR$X, VotesGR$Y),4,VotesGR$NDJune12,VotesGR$AllJune12,0.2966)
boxplot(res)

lctools documentation built on April 14, 2020, 6:04 p.m.