Toolkit to interact with the 'SOAP' web services of the
    'SEI' (Sistema Eletronico de Informacoes), the electronic system for
    document and process management widely used by Brazilian public
    administration bodies. Provides functions to build the 'SOAP' envelopes,
    perform the requests, handle 'SOAP' faults, and parse the 'XML' responses
    into data frames. Covers process and document queries, listing services,
    write operations (creating processes and documents, sending and signing
    off processes, blocks, deadlines and markers) and the permission services
    of the companion 'SIP' system. Note that access to the web services is
    restricted by the server to previously authorized network addresses.
    For more information about the 'SEI' system and its web services see
    <https://www.gov.br/gestao/pt-br/assuntos/processo-eletronico-nacional>.

Multiple interactive codes to view and analyze seismic data, via spectrum analysis, wavelet transforms, particle motion, hodograms.  Includes general time-series tools, plotting, filtering, interactive display.

Provides a set of R bindings for the 'Selenium 2.0 WebDriver'
    (see <https://www.selenium.dev/documentation/>
    for more information) using the 'JsonWireProtocol' (see
    <https://github.com/SeleniumHQ/selenium/wiki/JsonWireProtocol> for more
    information). 'Selenium 2.0 WebDriver' allows driving a web browser
    natively as a user would either locally or on a remote machine using
    the Selenium server it marks a leap forward in terms of web browser
    automation. Selenium automates web browsers (commonly referred to as
    browsers). Using RSelenium you can automate browsers locally or
    remotely.

A robust procedure is implemented to estimate means and covariance matrix of multiple variables with missing data using Huber weight and then to estimate a structural equation model.

Analyses sentiment of a sentence in English and assigns score to it. It can classify sentences to the following categories of sentiments:- Positive, Negative, very Positive, very negative, 
              Neutral. For a vector of sentences, it counts the number of sentences in each
              category of sentiment.In calculating the score, negation and various degrees
              of adjectives are taken into consideration. It deals only with English sentences.