Functions for interacting directly with the Nasdaq Data Link API to offer data in a number of formats usable in R, downloading a zip with all data from a Nasdaq Data Link database, and the ability to search. This R package uses the Nasdaq Data Link API. For more information go to <https://docs.data.nasdaq.com/>. For more help on the package itself go to <https://data.nasdaq.com/tools/r>.

Implement and enhance the performance of spatial fuzzy clustering using Fuzzy Geographically Weighted Clustering with various optimization algorithms, mainly from Xin She Yang (2014) <ISBN:9780124167438> with book entitled Nature-Inspired Optimization Algorithms. The optimization algorithm is useful to tackle the disadvantages of clustering inconsistency when using the traditional approach. The distance measurements option is also provided in order to increase the quality of clustering results. The Fuzzy Geographically Weighted Clustering with nature inspired optimisation algorithm was firstly developed by Arie Wahyu Wijayanto and Ayu Purwarianti (2014) <doi:10.1109/CITSM.2014.7042178> using Artificial Bee Colony algorithm.

NeuroAnatomy Toolbox (nat) enables analysis and visualisation of 3D
    biological image data, especially traced neurons. Reads and writes 3D images
    in NRRD and 'Amira' AmiraMesh formats and reads surfaces in 'Amira' hxsurf
    format. Traced neurons can be imported from and written to SWC and 'Amira'
    LineSet and SkeletonGraph formats. These data can then be visualised in 3D
    via 'rgl', manipulated including applying calculated registrations, e.g.
    using the 'CMTK' registration suite, and analysed. There is also a simple
    representation for neurons that have been subjected to 3D skeletonisation
    but not formally traced; this allows morphological comparison between
    neurons including searches and clustering (via the 'nat.nblast' extension
    package).

Extends package 'nat' (NeuroAnatomy Toolbox) by providing a
    collection of NBLAST-related functions for neuronal morphology comparison (Costa et al. (2016) <doi: 10.1016/j.neuron.2016.06.012>).