Implementation of the mid-n algorithms presented in 
             Wellek S (2015) <DOI:10.1111/stan.12063> Statistica Neerlandica 69, 358-373 for exact 
             sample size calculation for superiority trials with binary outcome.

Apply tests of multiple comparisons based
    on studentized 'midrange' and 'range' distributions. 
    The tests are: Tukey Midrange ('TM' test),
    Student-Newman-Keuls Midrange ('SNKM' test), 
    Means Grouping Midrange ('MGM' test) and 
    Means Grouping Range ('MGR' test). The first two tests were published by 
    Batista and Ferreira (2020) <doi:10.1590/1413-7054202044008020>. 
    The last two are being published.

Evolutionary black box optimization algorithms building on the
  'bbotk' package. 'miesmuschel' offers both ready-to-use optimization
  algorithms, as well as their fundamental building blocks that can be used to
  manually construct specialized optimization loops. The Mixed Integer Evolution
  Strategies as described by Li et al. (2013) <doi:10.1162/EVCO_a_00059> can be
  implemented, as well as the multi-objective optimization algorithms NSGA-II
  by Deb, Pratap, Agarwal, and Meyarivan (2002) <doi:10.1109/4235.996017>.

Impute the covariance matrix of incomplete data so that factor 
  analysis can be performed. Imputations are made using multiple imputation 
  by Multivariate Imputation with Chained Equations (MICE) and combined with 
  Rubin's rules. Parametric Fieller confidence intervals and nonparametric
  bootstrap confidence intervals can be obtained for the variance explained by 
  different numbers of principal components. The method is described in 
  Nassiri et al. (2018) <doi:10.3758/s13428-017-1013-4>.

Allows the user to estimate transition probabilities for
    migratory animals between any two phases of the annual cycle, using a
    variety of different data types. Also quantifies the strength of
    migratory connectivity (MC), a standardized metric to quantify the
    extent to which populations co-occur between two phases of the annual
    cycle. Includes functions to estimate MC and the more traditional
    metric of migratory connectivity strength (Mantel correlation)
    incorporating uncertainty from multiple sources of sampling error. For
    cross-species comparisons, methods are provided to estimate
    differences in migratory connectivity strength, incorporating
    uncertainty. See Cohen et al. (2018) <doi:10.1111/2041-210X.12916>,
    Cohen et al. (2019) <doi:10.1111/ecog.03974>, and Roberts et al.
    (2023) <doi:10.1002/eap.2788> for details on some of these methods.