Performs correlation matrix segmentation and applies a test
    procedure to detect highly correlated regions in gene expression.

Proposes an application for sequence prediction generalizing the similarity within the network of previous sequences.

A set of segregation-based indices and randomization methods to
            make robust environmental inequality assessments, as described in
            Schaeffer and Tivadar (2019) "Measuring Environmental Inequalities:
            Insights from the Residential Segregation Literature"
            <doi:10.1016/j.ecolecon.2019.05.009>.

Contains functions that help to determine event
    boundaries in event segmentation experiments by bootstrapping a critical
    segmentation magnitude under the null hypothesis that all key presses were
    randomly distributed across the experiment. Segmentation magnitude is
    defined as the sum of Gaussians centered at the times of the segmentation
    key presses performed by the participants. Within a participant, the maximum
    of the overlaid Gaussians is used to prevent an excessive influence of a
    single participant on the overall outcome (e.g. if a participant is pressing
    the key multiple times in succession). Further functions are included, such
    as plotting the results.

Fitting regression models where, in addition to possible linear terms, one or more covariates have segmented (i.e., broken-line or piece-wise linear) or stepmented (i.e. piece-wise constant) effects. Multiple breakpoints for the same variable are allowed. 
  The estimation method is discussed in Muggeo (2003, <doi:10.1002/sim.1545>) and 
  illustrated in Muggeo (2008, <https://www.r-project.org/doc/Rnews/Rnews_2008-1.pdf>). An approach for hypothesis testing is presented 
  in Muggeo (2016, <doi:10.1080/00949655.2016.1149855>), and interval estimation for the breakpoint is discussed in Muggeo (2017, <doi:10.1111/anzs.12200>). 
  Segmented mixed models, i.e. random effects in the change point, are discussed in Muggeo (2014, <doi:10.1177/1471082X13504721>).
  Estimation of piecewise-constant relationships and changepoints (mean-shift models) is 
  discussed in Fasola et al. (2018, <doi:10.1007/s00180-017-0740-4>).