Bayesian Monotonic Regression Using a Marked Point Process
Construction
An extended version of the nonparametric Bayesian monotonic regression procedure described in Saarela & Arjas (2011) <DOI:10.1111/j.1467-9469.2010.00716.x>, allowing for multiple additive monotonic components in the linear predictor, and time-to-event outcomes through case-base sampling. The extension and its applications, including estimation of absolute risks, are described in Saarela & Arjas (2015) <DOI:10.1111/sjos.12125>.

An extended version of the nonparametric Bayesian monotonic regression procedure described in Saarela & Arjas (2011) <DOI:10.1111/j.1467-9469.2010.00716.x>, allowing for multiple additive monotonic components in the linear predictor, and time-to-event outcomes through case-base sampling. The extension and its applications, including estimation of absolute risks, are described in Saarela & Arjas (2015) <DOI:10.1111/sjos.12125>. The package also implements the nonparametric ordinal regression model described in Saarela, Rohrbeck & Arjas <arXiv:2007.01390>.

c(person(given = "Frank", family = "Busing",
role = c("aut", "cre"),
email = "busing@fsw.leidenuniv.nl"),
person("Juan", "Claramunt Gonzalez",
role = "aut",
email = "j.claramunt.gonzalez@fsw.leidenuniv.nl"))
Frank Busing [aut, cre],
Juan Claramunt Gonzalez [aut]
A fast up-and-down-blocks implementation for the pool-adjacent-violators algorithm
for simple linear ordered monotone regression, including two spin-off functions
for unimodal and bivariate monotone regression.

The monotone package contains a fast up-and-down-blocks implementation for the pool-adjacent-violators algorithm
for simple linear ordered monotone regression, including two spin-off functions
for unimodal and bivariate monotone regression (see <doi:10.18637/jss.v102.c01>).

Test for Monotonicity in Expected Asset Returns, Sorted by
Portfolios
c(person(given = "Siegfried", family = "Köstlmeier", role = c("aut", "cre", "trl"), email = "siegfried.koestlmeier@gmail.com"))
Test for monotonicity in financial variables sorted by portfolios. It is conventional practice in empirical research to form portfolios of assets ranked by a certain sort variable. A t-test is then used to consider the mean return spread between the portfolios with the highest and lowest values of the sort variable. Yet comparing only the average returns on the top and bottom portfolios does not provide a sufficient way to test for a monotonic relation between expected returns and the sort variable. This package provides nonparametric tests for the full set of monotonic patterns by Patton, A. and Timmermann, A. (2010) <doi:10.1016/0304-4076(89)90094-8> and compares the proposed results with extant alternatives such as t-tests, Bonferroni bounds, and multivariate inequality tests through empirical applications and simulations.
lmtest, MASS, sandwich, stats, methods, utils