Makes it easy to download financial data from Yahoo Finance <https://finance.yahoo.com/>.

Provides Map, Reduce and Filter variants to generate jobs on batch
    computing systems like PBS/Torque, LSF, SLURM and Sun Grid Engine.
    Multicore and SSH systems are also supported. For further details see the
    project web page.

Batch process large language model (LLM) text completions using data frame rows, with support for OpenAI's 'GPT' (<https://chat.openai.com>), Anthropic's 'Claude' (<https://claude.ai>), and Google's 'Gemini' (<https://gemini.google.com>). Includes features such as local storage, metadata logging, API rate limiting delays, and a 'shiny' app addin.

Provides consistent batch means estimation of Monte
    Carlo standard errors.

Semi-supervised and unsupervised Bayesian mixture models that
  simultaneously infer the cluster/class structure and a batch correction.
  Densities available are the multivariate normal and the multivariate t.
  The model sampler is implemented in C++. This package is aimed at analysis of
  low-dimensional data generated across several batches. See Coleman et al.
  (2022) <doi:10.1101/2022.01.14.476352> for details of the model.

Handy frameworks, such as error handling and log generation, for batch scripts.
	Use case: in scripts running in remote servers, set error handling mechanism for downloading and uploading and record operation log.

Different adjustment methods for batch effects in biomarker data,
  such as from tissue microarrays. Some methods attempt to retain differences 
  between batches that may be due to between-batch differences in "biological"
  factors that influence biomarker values.

As a successor of the packages 'BatchJobs' and 'BatchExperiments',
    this package provides a parallel implementation of the Map function for high
    performance computing systems managed by schedulers 'IBM Spectrum LSF'
    (<https://www.ibm.com/products/hpc-workload-management>),
    'OpenLava' (<https://www.openlava.org/>), 'Univa Grid Engine'/'Oracle Grid
    Engine' (<https://www.univa.com/>), 'Slurm' (<https://slurm.schedmd.com/>),
    'TORQUE/PBS'
    (<https://adaptivecomputing.com/cherry-services/torque-resource-manager/>),
    or 'Docker Swarm' (<https://docs.docker.com/engine/swarm/>).
    A multicore and socket mode allow the parallelization on a local machines,
    and multiple machines can be hooked up via SSH to create a makeshift
    cluster. Moreover, the package provides an abstraction mechanism to define
    large-scale computer experiments in a well-organized and reproducible way.