Title: Collection of functions for matrix calculations
for probability, econometric and numerical analysis. There are
are useful for actuarial models such as pension mathematics.
This package is used for teaching and research purposes at the
Department of Finance and Risk Engineering, New York
University, Polytechnic Institute, Brooklyn, NY 11201.

Title: Collection of Functions for Matrix Calculations
Lancaster, P. (1969) Theory of Matrices. ISBN 978-0124355507.
Lay, D.C. (1995) Linear Algebra: And Its Applications. ISBN 978-0201845563.

Title: Statistics for Matrix Distributions
Authors@R: c(person("Martin", "Bladt", email = "martinbladt@gmail.com", role = c("aut", "cre")),
person("Jorge", "Yslas", email = "jorge.yslas1@gmail.com",
Description: Tools for homogeneous and in-homogeneous phase-type distributions.
Methods for functional evaluation, simulation and estimation using the
expectation-maximization (EM) algorithm are provided.
The methods of this package are based on the following references.
Asmussen, S., Nerman, O., & Olsson, M. (1996) <https://www.jstor.org/stable/4616418>,
Packaged: 2021-02-15 17:19:32 UTC; martinbladt

Packaged: 2021-02-26 08:39:46 UTC; martinbladt

Packaged: 2021-01-07 01:26:20 UTC; martinbladt

Packaged: 2021-06-17 16:35:14 UTC; martinbladt

Packaged: 2021-06-18 09:44:52 UTC; martinbladt

Packaged: 2021-08-25 15:17:01 UTC; martinbladt

person("Alaric", "Müller", email = "muelleralaric@gmail.com",
Description: Tools for phase-type distributions including the following variants:
continuous, discrete, multivariate, in-homogeneous, right-censored, and regression.
expectation-maximization (EM) algorithm are provided for all models.
Albrecher, H., Bladt, M., & Mueller, A. (2022) <arXiv:2207.01279>.
Packaged: 2022-09-12 17:26:44 UTC; martinbladt

Packaged: 2022-09-27 19:12:14 UTC; martinbladt

Packaged: 2022-10-15 23:49:21 UTC; martinbladt

Title: Matrix-based Partial Least Squares estimation
Authors@R: c(person("Mikko", "Rönkkö", role=c("aut", "cre"),
Description: matrixpls is implements Partial Least Squares Path Modeling algorithm and related algorithms. The algorithm implementations aim for computational efficiency using matrix algebra and covariance data. The package is designed toward Monte Carlo simulations and includes functions to perform simple Monte Carlo simulations.
Suggests: assertive, matrixcalc, plspm, simsem, boot, psych, lavaan,