Translates a CSS selector into an equivalent XPath
  expression. This allows us to use CSS selectors when working with
  the XML package as it can only evaluate XPath expressions. Also
  provided are convenience functions useful for using CSS selectors on
  XML nodes. This package is a port of the Python package 'cssselect'
  (<https://cssselect.readthedocs.io/>).

Fit and selects point pattern models based on minimum contrast, AIC and and goodness of fit.

Detection of outliers and influential errors using a latent variable model.

A user-friendly wrapper for web automation, using either
    'chromote' or 'selenium'. Provides a simple and consistent API to make
    web scraping and testing scripts easy to write and understand.
    Elements are lazy, and automatically wait for the website to be valid,
    resulting in reliable and reproducible code, with no visible impact on
    the experience of the programmer.

An implementation of 'W3C WebDriver 2.0'
  (<https://w3c.github.io/webdriver/>), allowing interaction
  with a 'Selenium Server' (<https://www.selenium.dev/documentation/grid/>)
  instance from 'R'. Allows a web browser to be automated from 'R'.

Provides the SELF criteria to learn causal structure. Please cite "Ruichu Cai, Jie Qiao, Zhenjie Zhang, Zhifeng Hao. SELF: Structural Equational Embedded Likelihood Framework for Causal Discovery. AAAI. 2018."

Execute the self-controlled case series (SCCS) design using observational 
  data in the OMOP Common Data Model. Extracts all necessary data from the database and 
	transforms it to the format required for SCCS. Age and season can be modeled
	using splines assuming constant hazard within calendar months. Event-dependent 
	censoring of the observation period can be corrected for. Many exposures can be
	included at once (MSCCS), with regularization on all coefficients except for the
	exposure of interest. Includes diagnostics for all major assumptions of the SCCS.

A probability tree allows to compute probabilities of
	     complex events, such as genotype probabilities in intermediate generations of inbreeding
	     through recurrent self-fertilization (selfing). This package implements functionality to compute
	     probability trees for two- and three-marker genotypes in the F2 to F7 selfing
	     generations. The conditional probabilities are derived automatically
	     and in symbolic form. The package also provides functionality to
	     extract and evaluate the relevant probabilities.