The Hypothesis tests for the means of independent or paired groups.
    This package investigates the normality assumption automatically.
    Then, it tests the hypothesis tests for two independent or paired group means
    by using parametric or non-parametric tests. It uses the Shapiro-Wilk test to
    test the normality assumption. For independent two groups, If data comes from
    the normal distribution, the package uses the Z or t-test according to whether
    variances are known. For paired groups, it uses paired t-test under normal data
    sets. If data does not come from the normal distribution, the package uses the
    Wilcoxon test for independent and paired cases.

Implementation of SAPEVO-M, a Group Ordinal Method for Multiple Criteria Decision-Making (MCDM). SAPEVO-M is an acronym for Simple Aggregation of Preferences Expressed by Ordinal Vectors Group Decision Making. This method provides alternatives ranking given decision makers' preferences: criteria preferences and alternatives preferences for each criterion.This method is described in Gomes et al. (2020) <doi: 10.1590/0101-7438.2020.040.00226524 >.

Access, modify, aggregate and plot data from the 'Sapfluxnet' project,
  the first global database of sap flow measurements.

In ecology, spatial data is often represented using polygons. These
  polygons can represent a variety of spatial entities, such as ecological
  patches, animal home ranges, or gaps in the forest canopy.  Researchers often
  need to determine if two spatial processes, represented by these polygons, are
  independent of each other. For instance, they might want to test if the home
  range of a particular animal species is influenced by the presence of a
  certain type of vegetation.  To address this, Godoy et al. (2022)
  (<doi:10.1016/j.spasta.2022.100695>) developed conditional Monte Carlo
  tests. These tests are designed to assess spatial independence while taking
  into account the shape and size of the polygons.

Functions for statistical analysis of point processes.