Format a number (or a list of numbers) to a string (or a
        list of strings) with SI prefix. Use SI prefixes as constants
        like (4 * milli)^2

Framework to build an individual tree simulator.

Provides extensions for package 'sitree' for allometric variables, growth, mortality, recruitment, management, tree removal and external modifiers functions.

An end-to-end toolkit for land use and land cover classification
    using big Earth observation data. Builds satellite image data cubes from cloud collections.
    Supports visualization methods for images and time series and 
    smoothing filters for dealing with noisy time series.
    Enables merging of multi-source imagery (SAR, optical, DEM).
    Includes functions for quality assessment of training samples using self-organized maps and  
    to reduce training samples imbalance. Provides machine learning algorithms including support vector machines, 
    random forests, extreme gradient boosting, multi-layer perceptrons,
    temporal convolution neural networks, and temporal attention encoders.
    Performs efficient classification of big Earth observation data cubes and includes 
    functions for post-classification smoothing based on Bayesian inference. 
    Enables best practices for estimating area and assessing accuracy of land change. 
    Includes object-based spatio-temporal segmentation for space-time OBIA.
    Minimum recommended requirements: 16 GB RAM and 4 CPU dual-core.

An iterative feature selection method that internally utilizes
    various Machine Learning methods that have embedded feature reduction in
    order to shrink down the feature space into a small and yet robust set.

Functions and utilities to perform
    Statistical Analyses in the Six Sigma way.
    Through the DMAIC cycle (Define, Measure, Analyze, Improve, Control),
    you can manage several Quality Management studies:
    Gage R&R, Capability Analysis, Control Charts, Loss Function Analysis,
    etc. Data frames used in the books "Six Sigma with R" [ISBN 978-1-4614-3652-2]
    and "Quality Control with R" [ISBN 978-3-319-24046-6], 
    are also included in the package.