squat 0.4.0
New features
- Adaptation to new API of fdacluster.
 
- Added rotation invariant elastic distance.
 
- Added no alignment option in distance matrix computation via
SRVF.
 
- Added roll-pitch-yaw representation.
 
- Added 
format()/print() pair
correctly. 
Minor improvements and bug
fixes
- Remove dependency to purrr in favor of base R
*apply() family to reduce dependency trail. 
- Replace furrr with future.apply
for consistency with the removal of purrr.
 
- Update roxygen version.
 
- Fix bug in predict from PCA with new data. Properly compute L2 inner
product.
 
- Fix bug in predict from prcomp object.
 
squat 0.3.0
New features
- Added 
S3 specialization of the
stats::predict() function for prcomp_qts
objects. 
- Added function 
qts2aats() which allows to switch from
quaternion to axis-angle representation of rotations. 
- Added usual operations 
+, -,
* and inverse_qts() for quaternion time series
using the Eigen
library. 
Small improvements
- Make sure quaternion geodesic mean is not flipped.
 
- Fix issues in PCA:
- avoid numerical overflows due to bad choice of 
k in
gam(); 
- improved documentation;
 
- Use same number of basis functions in uni- and multivariate
decompositions.
 
 
- Updated GHA scripts and 
README. 
- Fix bug related to Rcpp following RcppCore/Rcpp#1287.
 
squat 0.2.1
- Add 
use_fence robustification option; 
- Adapt to changes in fdacluster;
 
- Properly compute tangent spaces along mean QTS;
 
- Update News section of website.
 
squat 0.2.0
Major features:
- Added hierarichal clustering;
 
- Added DBSCAN clustering;
 
- Added distance matrix computation.
 
Minor improvements:
- Adapted code to match new API in fdacluster
package.
 
squat 0.1.0
Major statistical features
- A first API proposal with a class 
qts and a class
qts_sample for which a number of methods are properly
implemented. 
- Available statistical methods for QTS samples:
- random generation according to the Gaussian functional model via 
rnorm_qts(), 
scale(), 
mean(), 
median(), 
- distance matrix computation via 
distDTW()
(i.e. for now we use the dynamic time warping), 
- tangent principal component analysis via 
prcomp(), 
- k-means with optional alignment via 
kmeans(). 
 
- Added multiple ways of displaying samples of QTS.
 
- Added two example datasets.
 
Improvements
- Make all functions applicable to a single QTS also applicable to QTS
samples, with appropriate class for the output.
 
- Enable 
as_qts_sample() to generate a QTS sample of size
1 from a single QTS as input argument. 
- Rename 
change_points argument to the
plot.qts() function to better reflect its flexibility. 
- Added subset operator for QTS sample objects.
 
- Added 
append S3 method for QTS sample objects. 
- Added 
hemispherize() function to remove any
discontinuities in QTS due to quaternion flips. 
- Any parallelization computation is now handled using the futureverse
principles and, in particular, implemented through the use of the furrr
package.
 
squat 0.0.1
- Added a 
NEWS.md file to track changes to the
package. 
- Initial version.