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 <skalo@hua.gr>
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
providing 
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