Provides a function for measuring the difference between two independent or non-independent empirical distributions and returning a significance level of the difference.

Causal and statistical inference on an arbitrary treatment
    effect curve requires care in both estimation and inference.  This
    package, implements the Method of Direct Estimation and Inference as introduced in "Estimation and Inference on Nonlinear and Heterogeneous Effects" by Ratkovic and Tingley (2023) <doi:10.1086/723811>.  The method takes an outcome, variable of theoretical interest
    (treatment), and set of variables and then returns a partial
    derivative (marginal effect) of the treatment variable at each point
    along with uncertainty intervals. The approach offers two advances.
    First, a split-sample approach is used as a guard against over-fitting.
    Second, the method uses a data-driven interval derived from conformal
    inference, rather than relying on a normality assumption on the error
    terms.

A comprehensive collection of linkage methods for agglomerative
  hierarchical clustering on a matrix of proximity data (distances or
  similarities), returning a multifurcated dendrogram or multidendrogram.
  Multidendrograms can group more than two clusters when ties in proximity data
  occur, and therefore they do not depend on the order of the input data.
  Descriptive measures to analyze the resulting dendrogram are additionally
  provided.

Functions for MultiDimensional Feature Selection (MDFS):
 calculating multidimensional information gains, scoring variables,
 finding important variables, plotting selection results.
 This package includes an optional CUDA implementation that speeds up
 information gain calculation using NVIDIA GPGPUs.
 R. Piliszek et al. (2019) <doi:10.32614/RJ-2019-019>.

'MTrackJ' is an 'ImageJ' plugin for motion tracking and analysis (see 
    <https://imagescience.org/meijering/software/mtrackj/>). This package reads 
    and writes 'MTrackJ Data Files' ('.mdf', see 
    <https://imagescience.org/meijering/software/mtrackj/format/>). It supports
    2D data and read/writes cluster, point, and channel information. If desired, 
    generates track identifiers that are unique over the clusters.
    See the project page for more information and examples.