Endometrial

Data from a study about Endometrial Cancer

datasets

Provide users with a framework to learn the intricacies of the Hamiltonian Monte Carlo algorithm with hands-on experience by tuning and fitting their own models. All of the code is written in R. Theoretical references are listed below:.
Neal, Radford (2011) "Handbook of Markov Chain Monte Carlo" ISBN: 978-1420079418,
Betancourt, Michael (2017) "A Conceptual Introduction to Hamiltonian Monte Carlo" <arXiv:1701.02434>,
Thomas, S., Tu, W. (2020) "Learning Hamiltonian Monte Carlo in R" <arXiv:2006.16194>,
Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013) "Bayesian Data Analysis" ISBN: 978-1439840955,
Agresti, Alan (2015) "Foundations of Linear and Generalized Linear Models ISBN: 978-1118730034,
Pinheiro, J., Bates, D. (2006) "Mixed-effects Models in S and S-Plus" ISBN: 978-1441903174.

Samuel Thomas

hmclearn

Fit Statistical Models Using Hamiltonian Monte Carlo

Wanzhu Tu

Endometrial function

A data frame with 79 rows and 4 variables:<dl class="dl-horizontal">
 <dt>NV</dt><dd>Neovasculation risk factor indicator (0=Absent, 1=Present)</dd>
 <dt>PI</dt><dd>Pulsatility index of arteria uterina</dd>
 <dt>EH</dt><dd>Endometrium height</dd>
 <dt>HG</dt><dd>histology of patient (0=Low, 1=High)</dd>
</dl>

Format

Endometrial Cancer Dataset — Endometrial

A data frame with 79 rows and 4 variables:<dl class='dl-horizontal'>
 <dt>NV</dt><dd>Neovasculation risk factor indicator (0=Absent, 1=Present)</dd>
 <dt>PI</dt><dd>Pulsatility index of arteria uterina</dd>
 <dt>EH</dt><dd>Endometrium height</dd>
 <dt>HG</dt><dd>histology of patient (0=Low, 1=High)</dd>
</dl>

Endometrial: Endometrial Cancer Dataset

Description

Usage

Arguments

Format

References