A set of functions leading to multivariate response L1 regression. 
    This includes functions on computing Euclidean inner products and norms, 
    weighted least squares estimates on multivariate responses, function to compute 
    fitted values and residuals. This package is a companion to the book "U-Statistics,
    M-estimation and Resampling", by Arup Bose and Snigdhansu Chatterjee, to appear 
    in 2017 as part of the "Texts and Readings in Mathematics" (TRIM) series of 
    Hindustan Book Agency and Springer-Verlag.

Make requests from the US Treasury Fiscal Data API endpoints.

Forms a query to submit for US Treasury yield curve data, posting
    this query to the US Treasury web site's data feed service.  By default the
    download includes data yield data for 12 products from January 1, 1990,
    some of which are NA during this span.  The caller can pass parameters to
    limit the query to a certain year or year and month, but the full download
    is not especially large.  The download data from the service is in XML
    format.  The package's main function transforms that XML data into a numeric 
    data frame with treasury product items (constant maturity yields for 12 kinds 
    of bills, notes, and bonds) as columns and dates as row names. The function 
    returns a list which includes an item for this data frame as well as query-related
    values for reference and the update date from the service.

Three functions are provided: first function changes time from local to UTC, other changes from UTC to local and third returns difference between local and UTC. %h+% operator is also provided it adds hours to a time.

Process and print 'UTF-8' encoded international
    text (Unicode). Input, validate, normalize, encode, format, and
    display.

Functions for building customized ready-to-export tables for publication.

Tools for formatting and summarizing data for outcomes research.

A set of functions to aid in the production of visuals in ggplot2.

Construct and plot objective hierarchies and associated value and utility functions. 
  Evaluate the values and utilities and visualize the results as colored objective hierarchies or tables. 
  Visualize uncertainty by plotting median and quantile intervals within the nodes of objective hierarchies.
  Get numerical results of the evaluations in standard R data types for further processing.