Provides functions to analyse DNA fragment samples (i.e. derived from RFLP-analysis) and standalone BLAST report files (i.e. DNA sequence analysis).

Interface to the 'flsgen' neutral landscape generator <https://github.com/dimitri-justeau/flsgen>. It allows to
  - Generate fractal terrain;
  - Generate landscape structures satisfying user targets over landscape indices;
  - Generate landscape raster from landscape structures.

Tools for RFM (recency, frequency and monetary value) analysis. 
    Generate RFM score from both transaction and customer level data. Visualize the
    relationship between recency, frequency and monetary value using heatmap, 
    histograms, bar charts and scatter plots. Includes a 'shiny' app for 
    interactive segmentation. References:
    i. Blattberg R.C., Kim BD., Neslin S.A (2008) <doi:10.1007/978-0-387-72579-6_12>.

S3 implementation of the Random Forest MErging Procedure (RF-MEP), which combines two or more satellite-based datasets (e.g., precipitation products, topography) with ground observations to produce a new dataset with improved spatio-temporal distribution of the target field. In particular, this package was developed to merge different Satellite-based Rainfall Estimates (SREs) with measurements from rain gauges, in order to obtain a new precipitation dataset where the time series in the rain gauges are used to correct different types of errors present in the SREs. However, this package might be used to merge other hydrological/environmental gridded datasets with point observations. For details, see Baez-Villanueva et al. (2020) <doi:10.1016/j.rse.2019.111606>. Bugs / comments / questions / collaboration of any kind are very welcomed.

Fits cause-specific random survival forests for flexible
    multistate survival analysis with covariate-adjusted transition
    probabilities computed via product-integral. State transitions are 
    modeled by random forests. Subject-specific transition probability matrices 
    are assembled from predicted cumulative hazards using the product-integral formula.
    Also provides a standalone Aalen-Johansen nonparametric estimator as
    a covariate-free baseline. Supports arbitrary state spaces with any
    number of states (three or more) and any set of allowed transitions,
    applicable to clinical trials, disease progression, reliability
    engineering, and other domains where subjects move among discrete
    states over time. Provides per-transition feature importance,
    bias-variance diagnostics, and comprehensive visualizations. Handles
    right censoring and competing transitions. Methods are described in
    Ishwaran et al. (2008) <doi:10.1214/08-AOAS169> for random survival
    forests, Putter et al. (2007) <doi:10.1002/sim.2712> for multistate
    competing risks decomposition, and Aalen and Johansen (1978)
    <https://www.jstor.org/stable/4615704> for the nonparametric
    estimator.