A non-parametric test for multi-observer concordance and
    differences between concordances in (un)balanced data.

Onedimensional Normal (i.e. Gaussian) Mixture Models (S3) Classes,
   for, e.g., density estimation or clustering algorithms research and teaching;
   providing the widely used Marron-Wand densities.  Efficient random
   number generation and graphics. Fitting to data by efficient ML (Maximum
   Likelihood) or traditional EM estimation.

Provides the Arctic Ice Studio's Nord and Group of Seven inspired colour palettes for use with 'ggplot2' via custom functions.

The Nordklim dataset 1.0 is a unique and useful achievement for climate 
    analysis. It includes observations of twelve different climate elements from 
    more than 100 stations in the Nordic region, in time span over 100 years.
    The project contractors were NORDKLIM/NORDMET on behalf of the National 
    meteorological services in Denmark (DMI), Finland (FMI), Iceland (VI), 
    Norway (DNMI) and Sweden (SMHI).

Provides a SQLite-backed cell-level cache that can be used as a
    drop-in backend by the nordstat family of packages ('rKolada', 'rTrafa', and
    'pixieweb'). Designed for multi-user web applications where minimal fetch
    latency and asynchronous writes are required. Individual statistical
    values ("cells") are stored in a gatekeeper schema with a sidecar table
    for arbitrary metadata dimensions, enabling deduplication across
    overlapping queries.

An integrated set of functions for the analysis of 
  multivariate normal datasets with missing values, including implementation of
  the EM algorithm, data augmentation, and multiple imputation.

Enables correction for technical variance in raw quantitative reverse
  transcription polymerase chain reaction (qRT-PCR) data using the least
  squares-based NORMAgene data-driven normalization algorithm originally
  described by Heckmann et al. (2011) <doi:10.1186/1471-2105-12-250>.
  Performs normalization of raw crossing threshold values (CT) and also
  calculates relative variability metrics that can be used to assess the impact
  of normalization on variance.