initializeMCMCObject {AnaCoDa} | R Documentation |

`initializeMCMCObject`

initializes a MCMC object to
perform a model fitting for a parameter and model object.

initializeMCMCObject( samples, thinning = 1, adaptive.width = 100, est.expression = TRUE, est.csp = TRUE, est.hyper = TRUE, est.mix = TRUE )

`samples` |
Number of samples to be produced when running the MCMC algorithm. No default value. |

`thinning` |
The thinning interval between consecutive observations. If set to 1, every step will be saved as a sample. Default value is 1. |

`adaptive.width` |
Number that determines how often the acceptance/rejection
window should be altered. Default value is 100 samples.
Proportion of MCMC steps where the proposal distribution is adaptive can be set using |

`est.expression` |
Boolean that tells whether or not synthesis rate values should be estimated in the MCMC algorithm run. Default value is TRUE. |

`est.csp` |
Boolean that tells whether or not codon specific values should be estimated in the MCMC algorithm run. Default value is TRUE. |

`est.hyper` |
Boolean that tells whether or not hyper parameters
should be estimated in the MCMC algorithm run. Default value is TRUE.
Setting for expression noise parameter sepsilon can be overridden by setting |

`est.mix` |
Boolean that tells whether or not the genes' mixture element should be estimated in the MCMC algorithm run. Default value is TRUE. |

`initializeMCMCObject`

sets up the MCMC object
(monte carlo markov chain) and returns the object so a model fitting can be done.
It is important to note that est.expression and est.hyper will affect one another
negatively if their values differ.

mcmc Returns an intialized MCMC object.

## initializing an object of type mcmc samples <- 2500 thinning <- 50 adaptiveWidth <- 25 ## estimate all parameter types mcmc <- initializeMCMCObject(samples = samples, thinning = thinning, adaptive.width=adaptiveWidth, est.expression=TRUE, est.csp=TRUE, est.hyper=TRUE, est.mix = TRUE) ## do not estimate expression values, initial conditions will remain constant mcmc <- initializeMCMCObject(samples = samples, thinning = thinning, adaptive.width=adaptiveWidth, est.expression=FALSE, est.csp=TRUE, est.hyper=TRUE, est.mix = TRUE) ## do not estimate hyper parameters, initial conditions will remain constant mcmc <- initializeMCMCObject(samples = samples, thinning = thinning, adaptive.width=adaptiveWidth, est.expression=TRUE, est.csp=TRUE, est.hyper=FALSE, est.mix = TRUE)

[Package *AnaCoDa* version 0.1.4.4 Index]