Package for fitting Multi-Parameter Regression (MPR) models to right-censored survival data. These are flexible parametric regression models which extend standard models, for example, proportional hazards.

Fitting Multi-Parameter Regression (MPR) models to right-censored survival data. These are flexible parametric regression models which extend standard models, for example, proportional hazards. See Burke & MacKenzie (2016) <doi:10.1111/biom.12625> and Burke et al (2020) <doi:10.1111/rssc.12398>.

Multivariate probit model for binary/ordinal response
Harry Joe <harry@stat.ubc.ca>, Laing Wei Chou and Hongbin Zhang
Multivariate normal rectangle probabilities (positive
exchangeable, general, approximations);
MLE of regression and correlation
parameters in the multivariate binary/ordinal probit models:
exchangeable, AR(1), and unstructured correlation matrix.

Multivariate normal rectangle probabilities (positive
exchangeable, general, approximations); MLE of regression and
correlation parameters in the multivariate binary/ordinal
probit models: exchangeable, AR(1), and unstructured
correlation matrix.

Mass-Preserving Spline Functions for Soil Data
c(person("Lauren", "O'Brien", email = "obrlsoilau@gmail.com", role = c('aut', 'cre'), comment = c(ORCID = "0000-0002-7336-2171")),
person("Brendan", "Malone",  email = "brendan.malone@csiro.au",  role = c('ctb'), comment = c(ORCID = "0000-0002-0473-8518")),
person("Tomislav", "Hengl",  email = "tom.hengl@wur.nl",  role = c('ctb'), comment = c(ORCID = "0000-0002-9921-5129")),
person("Tom", "Bishop",  email = "t.bishop@usyd.edu.au",  role = c('ctb')),
person("David", "Rossiter",  email = "david.rossiter@wur.nl",  role = c('ctb')),
person("Dylan", "Beaudette",  email = "dylan.beaudette@ca.usda.gov",  role = c('ctb')))
A low-dependency implementation of GSIF::mpspline() <https://r-forge.r-project.org/scm/viewvc.php/pkg/R/mpspline.R?view=markup&revision=240&root=gsif>,
which applies a mass-preserving spline to soil attributes. Splining soil data
is a safe way to make continuous down-profile estimates of attributes measured
over discrete, often discontinuous depth intervals.
Lauren O'Brien [aut, cre] (<https://orcid.org/0000-0002-7336-2171>),
Brendan Malone [ctb] (<https://orcid.org/0000-0002-0473-8518>),
Tomislav Hengl [ctb] (<https://orcid.org/0000-0002-9921-5129>),
Tom Bishop [ctb],
David Rossiter [ctb],
Dylan Beaudette [ctb]