An 'RStudio' Addin wrapper for the 'mergen' package. This package employs artificial intelligence to convert data analysis questions into executable code, explanations, and algorithms. This package makes it easier to use Large Language Models in your development environment by providing a chat-like interface, while also allowing you to inspect and execute the returned code.

Aggregates a set of trees with the same leaves to create a consensus tree. The trees are typically 
  obtained via hierarchical clustering, hence the hclust format is used to encode both the aggregated trees and the final 
  consensus tree. The method is exact and proven to be O(nqlog(n)), n being the individuals and q being the number of trees to aggregate.

Implementation of two tools to merge Hardware Event Monitors (HEMs) from different subexperiments. Hardware Reading and Merging (HRM), which uses order statistics to merge; and MUlti-Correlation HEM (MUCH) which merges using a multivariate normal distribution. The reference paper for HRM is: S. Vilardell, I. Serra, R. Santalla, E. Mezzetti, J. Abella and F. J. Cazorla, "HRM: Merging Hardware Event Monitors for Improved Timing Analysis of Complex MPSoCs," in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 39, no. 11, pp. 3662-3673, Nov. 2020, <doi:10.1109/TCAD.2020.3013051>. For MUCH: S. Vilardell, I. Serra, E. Mezzetti, J. Abella, and F. J. Cazorla. 2021. "MUCH: exploiting pairwise hardware event monitor correlations for improved timing analysis of complex MPSoCs". In Proceedings of the 36th Annual ACM Symposium on Applied Computing (SAC '21). Association for Computing Machinery. <doi:10.1145/3412841.3441931>. This work has been supported by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 772773).

Fits linear, non-linear, and user-defined mixed effects regression models following 
  the framework developed by Crowther (2017) <arXiv:1710.02223>. 'merlin' can fit multivariate 
  outcome models of any type, each of which could be repeatedly measured (longitudinal), with 
  any number of levels, and with any number of random effects at each level. Standard 
  distributions/models available include the Bernoulli, Gaussian, Poisson, beta, 
  negative-binomial, and time-to-event/survival models include the exponential, 
  Gompertz, Royston-Parmar, Weibull and general hazard model. 'merlin' provides a 
  flexible predictor syntax, allowing the user to define variables, random effects, 
  spline and fractional polynomial functions, functions of 
  other outcome models, and any interaction between each of them. Non-linear and 
  time-dependent effects are seamlessly incorporated into the predictor. 'merlin' 
  allows multivariate normal random effects, which are integrated out using Gaussian 
  quadrature or Monte-Carlo integration. Note, 'merlin' is based on the 'Stata' package 
  of the same name, described in Crowther (2018) <arXiv:1806.01615>.