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high computation time

Hi @sevvandi,

the methodology proposed takes forever to run on a real case study, in both univariate and multivariate analysis.

Data used: 6 months of hourly data, 15.312 observations.
Computational time: more than 20 minutes then I stopped.

System Information:
Ubuntu 20
8 cpu
16gb ram

Vulnerability to absence of retiring r-spatial packages

00check.log
is a recent check log from running under _SP_EVOLUTION_STATUS_=2 without retiring r-spatial packages (suggested in this package) on the library path. The minimal correction is to check that the package namespaces can be loaded, and if not, do not run those parts of the examples. It would be safer in the longer term to replace retiring r-spatial packages with active r-spatial/rspatial packages. You use maptools::readShapePoly in a vignette, then tidy the imported object using broom - both of these are very outdated and fragile, and are marked deprecated. Note that maptools warns that it will be retired on loading (it will be archived in October 2023). If you use sf to read the data, you can use geom_sf to plot under ggplot2.

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