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Function to calculate Adaptive bandwidths according to Abramson’s smoothing regimen.
adaptive_bw( grid, events, lines, bw, trim_bw, method, kernel_name, max_depth, tol, digits, sparse, verbose )
A vector with the local bandwidths
A spatial grid to split the data within
A feature collection of points representing the events points
A feature collection of linestrings representing the network
The fixed kernel bandwidth (can also be a vector, the value returned will be a matrix in that case)
The maximum size of local bandwidths (can also be a vector, must match bw)
The method to use when calculating the NKDE
The name of the kernel to use
The maximum recursion depth
A float indicating the spatial tolerance when snapping events on lines
The number of digits to keep
A Boolean indicating if sparse matrix should be used
A Boolean indicating if update messages should be printed
#This is an internal function, no example provided
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