Orphaned on 2019-09-01 as deprecated use of C++98 was
not corrected in time.

person(given = "Alec L.",
family = "Robitaille",
role = c("aut", "cre"),
email = "robit.alec@gmail.com",
comment = c(ORCID = "0000-0002-4706-1762"))
Calculates distances from point locations to features.
The usual approach for eg. resource selection function analyses is to
generate a complete distance to features surface then sample it with your
observed and random points. Since these raster based approaches can be
pretty costly with large areas, and often lead to memory issues in R,
the distanceto package opts to compute these distances using
efficient, vector based approaches. As a helper, there's a decidedly
low-res raster based approach for visually inspecting your region's
distance surface. But the workhorse is distance_to.
fasterize, knitr, rmarkdown, spData, raster, tinytest
Alec L. Robitaille [aut, cre] (<https://orcid.org/0000-0002-4706-1762>)

Assessing Dissimilarity Between Multivariate Time Series
Provides tools to assess the dissimilarity between multivariate time-series. It is based on the psi measure described in "Numerical methods in Quaternary pollen analysis" (Birks and Gordon, 1985 <doi:10.1002/jqs.3390020110>), which computes dissimilarity constrained by sample order, but the original idea has been extended to work with any kind of multivariate time-series, no matter whether they are regular, irregular, aligned or unaligned. Furthermore, the package allows to assess the significance of dissimilarity values by applying a restricted permutation test, allows to measure the contribution of individual variables to dissimilarity, and offers tools to transfer attributes (generally time or age, but other are possible) between sequences based on the similarity of their samples.
plyr, grDevices, foreach, parallel, doParallel, fields,
viridis, viridisLite, RColorBrewer
devtools, formatR, kableExtra, magrittr, knitr, rmarkdown

Provides tools to assess the dissimilarity between multivariate time-series. It is based on the psi measure described  by Birks and Gordon (1985 <doi:10.1002/jqs.3390020110>), which computes dissimilarity between irregular time-series constrained by sample order. However, in this package the original idea has been extended to work with any kind of multivariate time-series, no matter whether they are regular, irregular, aligned or unaligned. Furthermore, the package allows to assess the significance of dissimilarity values by applying a restricted permutation test, allows to measure the contribution of individual variables to dissimilarity, and offers tools to transfer attributes (generally time or age, but other are possible) between sequences based on the similarity of their samples.
plyr, grDevices, foreach, parallel, doParallel, fields,
viridis, RColorBrewer, data.table, iterators, arrangements