Imports: colorspace, MASS, pcaPP, fda, pdfCluster, ecp, strucchange,

person("Han Lin", "Shang", email="hanlin.shang@mq.edu.au", role=c("aut", "cre", "cph"), comment = c(ORCID = "0000-0003-1769-6430"))
Maintainer: Han Lin Shang <hanlin.shang@mq.edu.au>

Packaged: 2020-09-25 11:45:42 UTC; hanlinshang

e1071, psych, fGarch, KernSmooth, vars, boot, fdapace,

Title: Spectral Density Estimation and Comparison for Functional Time
Authors@R: person("Shahin", "Tavakoli", email = "s.tavakoli@statslab.cam.ac.uk", role = c("aut", "cre"))
Description: Functions for estimating spectral density operator of functional
time series (FTS) and comparing the spectral density operator of two
functional time series, in a way that allows detection of differences of
the spectral density operator in frequencies and along the curve length.

Title: Framework for Unified Estimation in Lognormal Models
Description: Lognormal models have broad applications in various research areas such as economics, actuarial science, biology, environmental science and psychology. The estimation problem in lognormal models has been extensively studied. This R package 'fuel' implements thirty-eight the existing and newly proposed estimators. See Zhang, F., and Gou, J. (2020), A unified framework for estimation in lognormal models, Technical report.

Description: Lognormal models have broad applications in various research areas such as economics, actuarial science, biology, environmental science and psychology. The estimation problem in lognormal models has been extensively studied. This R package 'fuel' implements thirty-nine existing and newly proposed estimators. See Zhang, F., and Gou, J. (2020), A unified framework for estimation in lognormal models, Technical report.

Description: Fuel economy data from the EPA, 1985-2015, conveniently

Description: Fuel economy data from the EPA, 1985-2015,
conveniently packaged for consumption by R users.

Title: FUzzy GEnetic, a machine learning algorithm to construct
Description: This is an evolutionary algorithm for fuzzy systems, a
genetic algorithm is used to construct a fuzzy system able to
fit the given training data.  This fuzzy system can then be
used as a prediction model, it's composed of fuzzy logic rules
that provide a good lingustic representation.
Packaged: 2012-08-08 12:58:32 UTC; alexandre