HiClimR 2.2.1
- Updated package website
 
- Updated package 
DESCRIPTION and
README 
- Updated package dependencies and 
WORDLIST 
- Style and format Fortran code
 
HiClimR 2.2.0
- Fixed NOTE: Found (possibly) invalid URLs
 
HiClimR 2.1.9
- Updated citation in package DESCRIPTION
 
- Updated NAMESPACE and documentation
 
- Fixed spelling errors
 
- Updated lifecycle URL in the README
 
HiClimR 2.1.8
- Code cleanup and formatting
 
- Removed HISTORY comments from source code
 
- Replaced 
1:n expressions with
seq_len(n) 
- Updated citation, manual, and user information
 
- Updated documents after code formatting
 
- Updated package DESCRIPTION and added reference DOI
 
- Updated package URL: https://hsbadr.github.io/HiClimR/
 
- README: Updated README.md and added NEWS.md
 
HiClimR 2.1.7
- Updated package DESCRIPTION and author information
 
- Updated copyright year to 2021
 
- README: Added Markdown badges
 
- README: Added Digital Object Identifier (DOI) badge
 
- README: Linked version and download badges to CRAN
 
- README: Updated URLs
 
HiClimR 2.1.6
- README: Added CRAN downloads badge
 
- R: Fix non-informative failure for unsupported input of a
vector
 
HiClimR 2.1.5
- R: Use 
inherits() to check class inheritance 
HiClimR 2.1.4
- Added vignette for HiClimR Bug Reporting
 
HiClimR2nc: Updated documentation and examples 
- man: Use 
\code{} instead of \bold{} for
classes 
HiClimR 2.1.3
- Fixed spelling errors and allowed custom words
 
HiClimR2nc: Fixed timeseries variable definition 
README: Link HiClimR to CRAN
package page 
HiClimR 2.1.2
- Fixed example ERROR in CRAN checks
 
- Added example to export NetCDF-4 file
 
- Updated dependencies and suggested packages
 
HiClimR 2.1.1
fastCor: Fixed row/col names of the correlation
matrix 
fastCor: Cleaned up zero-variance data check 
- Examples: Minor comment update
 
HiClimR 2.1.0
- Supported contiguity constraint based on geographic distance
 
- Exporting region map and mean timeseries into NetCDF-4 file
 
- Replaced 
multi-variate with
multivariate 
- Renamed 
weightedVar to weightMVC 
- Updated citation information
 
- Updated and cleaned up package 
DESCRIPTION 
- Updated and cleaned up 
README 
HiClimR 2.0.0
- Fixed NOTE: Registering native routines
 
fastCor: Removed zero-variance data 
fastCor: Introduced optBLAS 
fastCor: Code cleanup 
- Reformatted R source code
 
- Updated and fixed the examples
 
- Updated CRU TS dataset citation
 
- Updated 
README and all URLs 
HiClimR 1.2.3
- Fixed 
geogMask confusing country codes/names 
- Fixed 
geogMask filtering InDispute
areas 
- Corrected data construction in the user manual
x should be created using
as.vector(t(x0)) 
x0 is the n by m original data matrix 
n = length(unique(lon)) and
m = length(unique(lat)) 
 
coarseR now returns the original row numbers 
- Minor 
README corrections and updates 
HiClimR 1.2.2
- Changes for 
Undefined global functions 
- Checking geographic masking output
 
- Minor 
README corrections and updates 
HiClimR 1.2.1
- Updating variance for multivariate clustering
 
- More plotting options (
pch and cex) 
geogMask supports ungridded data 
- Updated user manual with the following notes:
- longitudes takes values from 
-180 to 180
(not 0 to 360) 
- for gridded data, the rows of input data matrix for each variable is
ordered by longitudes
- check 
rownames(TestCase$x) for example!
- each row represents a station (grid point)
 
- row name is in the form of 
longitude,latitude 
 
 
 
- Minor 
verbose fixes and updates 
- Minor 
README corrections and updates 
- Citation updated: technical paper has been published
 
HiClimR 1.2.0
- Multivariate clustering (MVC)
- the input matrix 
x can now be a list of matrices (one
matrix for each variable)
length(x) = nvars where nvars is the
number of variables 
- number of rows 
N = number of objects (e.g., stations)
to be clustered 
- number of columns 
M may vary for each variables
- e.g., different temporal periods or record lengths
 
 
 
- Each variable is separately preprocessed to allow for all possible
options
- preprocessing is specified by lists with length of
nvars (number of variables)
length(meanThresh) = length(x) = nvars 
length(varThresh) = length(x) = nvars 
length(detrend) = length(x) = nvars 
length(standardize) = length(x) = nvars 
length(weightMVC) = length(x) = nvars 
 
- filtering with 
meanThresh and varThresh
thresholds 
- detrending with 
detrend option, if requested 
- standardization with 
standardize option, if requested
- strongly recommended since variables may have different
magnitudes
 
 
- weighting by the new 
weightMVC option (default is
1) 
- combining variables by column (for each object: spatial points or
stations)
 
- applying PCA (if requested) and computing the
correlation/dissimilarity matrix
 
 
 
- Preliminary big data support
- function 
fastCor can now split the data matrix into
nSplit splits 
- adds a logical parameter 
upperTri to
fastCor function
- computes only the upper-triangular half of the
correlation/dissimilarity matrix
 
- it includes all required information since the
correlation/dissimilarity matrix is symmetric
 
- this almost halves memory use, which can be very important for big
data.
 
 
- fixes “integer overflow” for very large number of objects to be
clustered
 
 
- Adds a logical parameter 
verbose for printing
processing information 
- Adds a logical parameter 
dendrogram for plotting
dendrogram 
- Uses 
\dontrun{} to skip time-consuming examples
- for more examples: https://github.com/hsbadr/HiClimR#examples
 
 
- Backward compatibility with previous versions
 
- The user manual is updated and revised
 
HiClimR 1.1.6
- Setting minimum 
k = 2, for objective tree cutting
- this addresses an issue caused by undefined 
k = NULL in
validClimR function 
- when all inter-cluster correlations are significant at the
user-specified significance level
 
 
- Code reformatting using 
formatR 
- Package description and URLs have been revised
 
- Source code is now maintained on GitHub by authors
 
HiClimR 1.1.5
- Updating description, URL, and citation info
 
HiClimR 1.1.4
- Addresses an issue for zero-length mask vector:
Error in -mask : invalid argument to unary operator
- this error was introduced in v1.1.2+ after fixing the data-mean
bug
 
 
HiClimR 1.1.3
- The user manual is revised
 
lonSkip and latSkip renamed to
lonStep and latStep, respectively 
- Minor bug fixes
 
HiClimR 1.1.2
- A bug has been fixed where data mean is added to centered data if
standardize = FALSE
- objective tree cut and 
data component are now corrected
- to match input parameters especially when clustering of raw
data
 
- centered data was used in previous versions
 
 
 
HiClimR 1.1.1
- Minor bug fixes and memory optimizations especially for the
geographic masking function 
geogMask 
- The limit for data size has been removed (use with caution)
 
- A logical parameter 
InDispute is added to
geogMask function to optionally consider areas in dispute
for geographic masking by country 
HiClimR 1.1.0
- Code cleanup and bug fixes
 
- An issue with 
fastCor function that degrades its
performance on 32-bit machines has been fixed
- A significant performance improvement can only be achieved when
building R on 64-bit machines with an optimized 
BLAS
library, such as ATLAS, OpenBLAS, or the
commercial Intel MKL 
 
- The citation info has been updated to reflect the current status of
the technical paper
 
HiClimR 1.0.9
- Minor changes and fixes for CRAN
 
- For memory considerations,
- smaller test case with 1 degree resolution instead of 0.5
degree
 
- the resolution option (
res parameter) in geographic
masking is removed 
- Mask data is only available in 0.1 degree (~10 km) resolution
 
 
LazyLoad and LazyData are enabled in the
description file 
- The 
worldMask and TestCase data are
converted to lists to avoid conflicts of variable names
(lon, lat, info, and
mask) with lazy loading 
HiClimR 1.0.8
- Code cleanup and bug fixes
 
- Region maps are unified for both gridded and ungridded data
 
HiClimR 1.0.7
- Hybrid hierarchical clustering feature that utilizes the pros of the
available methods
- especially the better overall homogeneity in Ward’s method and the
separation and objective tree cut of the regional linkage method.
 
- The logical parameter 
hybrid is added to enable a
second clustering step
- using 
regional linkage for reconstructing the upper
part of the tree at a cut 
- defined by 
kH (number of clusters to restart with using
the regional linkage method) 
- If 
kH = NULL, the tree will be reconstructed for the
upper part with the first merging cost larger than the mean merging cost
for the entire tree
- merging cost is the loss of overall homogeneity at each merging
step
 
 
 
 
- If hybrid clustering is requested, the updated upper-part of the
tree will be used for cluster validation.
 
HiClimR 1.0.6
- Code cleanup and bug fixes
 
HiClimR 1.0.5
- Code cleanup and bug fixes
 
- Adds support to generate region maps for ungridded data
 
HiClimR 1.0.4
- Code cleanup and bug fixes
 
- The 
coarseR function is called inside the core
HiClimR function 
- Adds 
coords component to the output tree for the
longitude and latitude coordinates
- they may be changed by coarsening
 
 
validClimR function does not require lon
and lat arguments
- they are now available in the output tree (
coords
component) 
 
HiClimR 1.0.3
- Code cleanup and bug fixes
 
- One main/wrapper function 
HiClimR internally calls all
other functions 
- Unified component names for all functions
 
- Objective tree cut is supported only for the 
regional
linkage method
- Otherwise, the number of clusters 
k should be
specified 
 
- The new clustering method has been renamed from 
HiClimR
to regional linkage method 
HiClimR 1.0.2
- Code cleanup and bug fixes.
 
- adds a new feature that to return the preprocessed data used for
clustering, by a logical argument 
retData.
- the data will be returned in a component
data of the
output tree 
- this can be used to utilize 
HiCLimR preprocessing
options for further analysis 
 
- Ordered regions vector for the selected number of clusters are now
returned in the 
region component
- length equals the number of spatial elements 
N 
 
HiClimR 1.0.1
- Code cleanup and bug fixes
 
- Adds a new feature in 
validCLimR that enables users to
exclude very small clusters from validation indices
interCor, intraCor, diffCor, and
statSum, by setting a value for the minimum cluster size
(minSize > 1)
- the excluded clusters can be identified from the output of
validClimR in clustFlag component, which takes
a value of 1 for valid clusters or 0 for
excluded clusters 
- in 
HiClimR (currently, regional linkage)
method, noisy spatial elements (or stations) are isolated in very
small-size clusters or individuals since they do not correlate well with
any other elements 
- this should be followed by a quality control step
 
 
- Adds 
coarseR function for coarsening spatial resolution
of the input matrix x 
HiClimR 1.0.0
- Initial version of 
HiClimR package that modifies
hclust function in stats library 
- Adds a new clustering method to the set of available methods
 
- The new method is explained in the context of a spatiotemporal
problem, in which 
N spatial elements (e.g., stations) are
divided into k regions, given that each element has
observations (or timeseries) of length M
- minimizes the inter-regional correlation between region means
 
- modifies 
average update formulae by incorporating the
standard deviation of the mean of the merged region 
- a function of the correlation between the individual regions, and
their standard deviations before merging
 
- equals the average of their standard deviations if and only if the
correlation between the two merged regions is 
100%. 
- in this special case, the new method is reduced to the classic
average linkage clustering method 
 
- Several features are included to facilitate spatiotemporal analysis
applications:
- options for preprocessing and postprocessing
 
- efficient code execution for large datasets.
 
- cluster validation function 
validClimR 
- implements an objective tree cut to find an optimal number of
clusters
 
 
- Applicable to any correlation-based clustering