A recently proposed Bayesian BIN model disentangles the underlying processes 
    that enable forecasters and forecasting methods to improve, decomposing forecasting accuracy into 
    three components: bias, partial information, and noise. By describing the differences between two 
    groups of forecasters, the model allows the user to carry out useful inference, such as calculating 
    the posterior probabilities of the treatment reducing bias, diminishing noise, or increasing information.
    It also provides insight into how much tamping down bias and noise in judgment or enhancing the efficient 
    extraction of valid information from the environment improves forecasting accuracy. This package provides 
    easy access to the BIN model. For further information refer to the paper Ville A. Satopää, Marat Salikhov,
    Philip E. Tetlock, and Barbara Mellers (2021) "Bias, Information, Noise: The BIN 
    Model of Forecasting" <doi:10.1287/mnsc.2020.3882>.

Utilities to process, organize and explore protein structure,
    sequence and dynamics data. Features include the ability to read and write
    structure, sequence and dynamic trajectory data, perform sequence and structure
    database searches, data summaries, atom selection, alignment, superposition,
    rigid core identification, clustering, torsion analysis, distance matrix
    analysis, structure and sequence conservation analysis, normal mode analysis,
    principal component analysis of heterogeneous structure data, and correlation
    network analysis from normal mode and molecular dynamics data. In addition,
    various utility functions are provided to enable the statistical and graphical
    power of the R environment to work with biological sequence and structural data.
    Please refer to the URLs below for more information.

Contains all the necessary tools to process audio recordings of
             various formats (e.g., WAV, WAC, MP3, ZC), filter noisy files, 
             display audio signals, detect and extract automatically acoustic
             features for further analysis such as classification.