Perform common dendrometry operations such as inventory preparing, and inventory data analysis.

Allows user to conduct a simulation based quantitative
             bias analysis using covariate structures generated with individual-level
             data to characterize the bias arising from unmeasured confounding. Users
             can specify their desired data generating mechanisms to simulate data
             and quantitatively summarize findings in an end-to-end application
             using this package.

It provides users with a wide range of tools to simulate, estimate, analyze, and visualize the dynamics of stochastic differential systems in both forms Ito and Stratonovich. Statistical analysis with parallel Monte Carlo and moment equations methods of SDEs <doi:10.18637/jss.v096.i02>. Enabled many searchers in different domains to use these equations to modeling practical problems in financial and actuarial modeling and other areas of application, e.g., modeling and simulate of first passage time problem in shallow water using the attractive center (Boukhetala K, 1996) ISBN:1-56252-342-2.

Provides tools for simulating spatially dependent predictors (continuous or binary),
    which are used to generate scalar outcomes in a (generalized) linear model framework. Continuous
    predictors are generated using traditional multivariate normal distributions or Gauss Markov random
    fields with several correlation function approaches (e.g., see Rue (2001) <doi:10.1111/1467-9868.00288>
    and Furrer and Sain (2010) <doi:10.18637/jss.v036.i10>), while binary predictors are generated using
    a Boolean model (see Cressie and Wikle (2011, ISBN: 978-0-471-69274-4)). Parameter vectors 
	exhibiting spatial clustering can also be easily specified by the user.

Monitoring reporting rates of subject-level clinical events (e.g.
  adverse events, protocol deviations) reported by clinical trial sites is an
  important aspect of risk-based quality monitoring strategy. Sites that are 
  under-reporting or over-reporting events can be detected using bootstrap
  simulations during which patients are redistributed between sites. Site-specific
  distributions of event reporting rates  are generated that are used to assign
  probabilities to the observed reporting rates.
  (Koneswarakantha 2024 <doi:10.1007/s43441-024-00631-8>).