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.

Rserve is a versatile, scalable server enabling the
	     efficient use of R from other applications through
	     variety of protocols including QAP, WebSockets, HTTP
	     and HTTPS. It acts as a server (TCP/IP or local sockets) 
	     which allows binary requests to be sent to R. Every
	     connection has a separate workspace and working
	     directory. Client-side implementations are available
	     for many popular languages allowing applications
	     to use facilities of R without the need of linking to
	     the R binary. Rserve supports remote connections,
	     user authentication and file transfer. A simple R client
	     is included in this package as well. It also supports
	     OCAP mode for secure remote procedure calls,
	     including support for full event loop, asynchronous
	     results/graphics and console I/O.

A report of statistical findings (RSF) project template is
    generated using a 'bookdown' format. 'YAML' fields can be further
    customized. Additional helper functions provide extra features to the
    RSF.

Slow Feature Analysis (SFA), ported to R based on
    'matlab' implementations of SFA: 'SFA toolkit' 1.0 by Pietro Berkes and 'SFA toolkit'
    2.8 by Wolfgang Konen.

This is a collection of functions designed for simulating, estimating and forecasting seasonal functional autoregressive time series of order one. These methods are addressed in the manuscript: <https://www.monash.edu/business/ebs/research/publications/ebs/wp16-2019.pdf>.