Comprehensive set of tools for analyzing and manipulating functional
 data with non-uniform lengths. This package addresses two common scenarios in
 functional data analysis: Variable Domain Data, where the observation domain
 differs across samples, and Partially Observed Data, where observations are
 incomplete over the domain of interest. 'VDPO' enhances the flexibility and
 applicability of functional data analysis in 'R'.
 See Amaro et al. (2024) <doi:10.48550/arXiv.2401.05839>.

Although model selection is ubiquitous in scientific discovery, the stability and uncertainty of the selected model is often hard to evaluate. How to characterize the random behavior of the model selection procedure is the key to understand and quantify the model selection uncertainty. This R package offers several graphical tools to visualize the distribution of the selected model. For example, Gplot(), Hplot(), VDSM_scatterplot() and VDSM_heatmap(). To the best of our knowledge, this is the first attempt to visualize such a distribution. About what distribution of selected model is and how it work please see Qin,Y.and Wang,L. (2021) "Visualization of Model Selection Uncertainty" <https://homepages.uc.edu/~qinyn/VDSM/VDSM.html>.

Provides statistical methods for the design and analysis of a calibration study, which aims for calibrating measurements using two different methods. The package includes sample size calculation, sample selection,  regression analysis with error-in measurements and change-point regression. The method is described in Tian, Durazo-Arvizu, Myers, et al. (2014) <DOI:10.1002/sim.6235>.

Applies affine and similarity transformations on vector spatial data (sp objects). Transformations can be defined from control points or directly from parameters. If redundant control points are provided Least Squares is applied allowing to obtain residuals and RMSE.

Automates set operations (i.e., comparisons of overlap) between multiple vectors.
    It also contains a function for automating reporting in 'RMarkdown', by generating markdown output for easy analysis, as well as an 'RMarkdown' template for use with 'RStudio'.