Commit f5d20cf6 authored by Gilles Kratzer's avatar Gilles Kratzer
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update vignette/readme

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## Quick start
To install `mcmabn` you need two R packages: [abn](https://CRAN.R-project.org/package=abn) and [gRbase](https://CRAN.R-project.org/package=gRbase) that requires libraries stored not stored on [CRAN](https://cran.r-project.org/) but on [bioconductor](http://www.bioconductor.org/):
To install `mcmabn` you need two R packages: [abn](https://CRAN.R-project.org/package=abn) and [gRbase](https://CRAN.R-project.org/package=gRbase) that requires libraries stored not stored on [CRAN](https://cran.r-project.org/) but on [bioconductor](http://www.bioconductor.org/). Hence you **must** install these packages **before** installing `mcmcabn`:
``` r
if (!requireNamespace("BiocManager", quietly = TRUE))
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We believe that having those three algorithms in a unique function with user adjustable relative frequencies could only lead to better results. Indeed, those three algorithms work very differently. Indeed, the MC^3 is very stable and sample efficiently the nearby region. The REV and MBR could produce large MCMC jumps but different then possibly complementary.
The general method is the Metropolis Hasting algorithm. Essentially, it is a sequential application of two steps:
1. a new DAG is proposed from some proposal distribution Q
2. the proposed DAG is accepted with some acceptance probability A
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