Functions and Datasets designed to support teaching of
regression with applications to Marketing and Finance

Functions and Datasets designed to support teaching of regression with applications to Marketing and Finance

Simulation and Reconstruction of PET Images
Joern Schulz <jschulz78@web.de>
Peter Toft <pto@imm.dtu.dk>
Jesper James Jensen <jjj@oedan.dk>
Peter Philipsen <pap@imm.dtu.dk>
The R-package 'adimpro' (for reading and writing some
graphic formats, it is used in the demos too).
This package implements different analytic/direct and
iterative reconstruction methods of Peter Toft. It also
offer the possibility to simulate PET data.
GPL version 2 or newer. This library is Copyright (C) 2007
by Joern Schulz and Peter Toft.

Joern Schulz <jschulz78@web.de> Peter Toft <pto@imm.dtu.dk>
Jesper James Jensen <jjj@oedan.dk> Peter Philipsen
<pap@imm.dtu.dk>
The R-package 'adimpro' (for reading and writing some graphic
formats, it is used in the demos too).
This package implements different analytic/direct and
iterative reconstruction methods of Peter Toft. It also offer
the possibility to simulate PET data.
This package is Copyright (C) 2006-2009 by Joern Schulz and
Peter Toft.

This package is Copyright (C) 2006-2010 by Joern Schulz and
Peter Toft.

Implementation of different analytic/direct and
iterative reconstruction methods of radon transformed data
such as PET data. It also offer the possibility to simulate PET data.

Joern Schulz <jschulz78@web.de>,
Peter Toft <pto@imm.dtu.dk>,
Jesper James Jensen <jjj@oedan.dk>,
Peter Philipsen <pap@imm.dtu.dk>
R (>= 3.2.0), adimpro (>= 0.8.2), grDevices, graphics, stats,
utils
This package is Copyright (C) 2006-2018 by Joern Schulz and
Peter Toft.

c(
person(given = "Ville",
family = "Kinnula",
role = c("aut"),
email = "ville.kinnula@helsinki.fi",
comment = c()),
person(given = "Jing",
family = "Tang",
role = c("ctb"),
email = "jing.tang@helsinki.fi",
comment = c(ORCID = "0000-0001-7480-7710")),
person(given = "Ali",
family = "Amiryousefi",
role = c("aut", "cre"),
email = "ali.amiryousefi@helsinki.fi",
comment = c(ORCID = "0000-0002-6317-3860")))
Bayesian supervised predictive classifiers, hypothesis testing, and parametric estimation under Partition Exchangeability are implemented. The two classifiers presented are the marginal classifier (that assumes test data is i.i.d.) next to a more computationally costly but accurate simultaneous classifier (that finds a labelling for the entire test dataset at once based on simultanous use of all the test data to predict each label). We also provide the Maximum Likelihood Estimation (MLE) of the only underlying parameter of the partition exchangeability generative model as well as hypothesis testing statistics for equality of this parameter with a single value, alternative, or multiple samples. We present functions to simulate the sequences from Ewens Sampling Formula as the realisation of the Poisson-Dirichlet distribution and their respective probabilities.
Ville Kinnula [aut],
Jing Tang [ctb] (<https://orcid.org/0000-0001-7480-7710>),
Ali Amiryousefi [aut, cre] (<https://orcid.org/0000-0002-6317-3860>)