Set of functions designed to solve inverse problems. The direct problem is used to calculate a cost function to be minimized.
Here are listed some papers using Inverse Problems solvers and sensitivity analysis:
(Jader Lugon Jr.; Antonio J. Silva Neto 2011) <doi:10.1590/S1678-58782011000400003>.
(Jader Lugon Jr.; Antonio J. Silva Neto; Pedro P.G.W. Rodrigues 2008) <doi:10.1080/17415970802082864>.
(Jader Lugon Jr.; Antonio J. Silva Neto; Cesar C. Santana 2008) <doi:10.1080/17415970802082922>.

Bayesian Inference for A|B and Bandit Marketing Tests
Uses simple Bayesian conjugate prior update rules to calculate
the win probability of each option, value remaining in the test, and
percent lift over the baseline for various marketing objectives.
References:
Fink, Daniel (1997) "A Compendium of Conjugate Priors" <doi:10.1.1.157/5540>.
Stucchio, Chris (2015) "Bayesian A/B Testing at VWO" <http://cdn2.hubspot.net/hubfs/310840/VWO_SmartStats_technical_whitepaper.pdf>.
purrr, dplyr, tidyr, magrittr, tibble, rlang
spelling, knitr, testthat (>= 2.1.0), rmarkdown

Uses simple Bayesian conjugate prior update rules to calculate
the win probability of each option, value remaining in the test, and
percent lift over the baseline for various marketing objectives.
References:
Fink, Daniel (1997) "A Compendium of Conjugate Priors" <https://www.johndcook.com/CompendiumOfConjugatePriors.pdf>.
Stucchio, Chris (2015) "Bayesian A/B Testing at VWO" <http://cdn2.hubspot.net/hubfs/310840/VWO_SmartStats_technical_whitepaper.pdf>.

purrr, dplyr, tidyr (>= 1.0.0), magrittr, tibble, rlang

Uses simple Bayesian conjugate prior update rules to calculate
the win probability of each option, value remaining in the test, and
percent lift over the baseline for various marketing objectives.
References:
Fink, Daniel (1997) "A Compendium of Conjugate Priors" <https://www.johndcook.com/CompendiumOfConjugatePriors.pdf>.
Stucchio, Chris (2015) "Bayesian A/B Testing at VWO" <https://cdn2.hubspot.net/hubfs/310840/VWO_SmartStats_technical_whitepaper.pdf>.