semiauto.abc {abctools} | R Documentation |

## Performs semi-automatic ABC based on summary statistics regression.

### Description

Performs semi-automatic ABC based on summary statistics regression.

### Usage

```
semiauto.abc(obs, param, sumstats, obspar=NULL, abcmethod = abc,
saprop = 0.5, abcprop = 0.5, overlap = FALSE, satr = list(),
plot = FALSE, verbose = TRUE, do.err = FALSE, final.dens = FALSE,
errfn = rsse, ...)
```

### Arguments

`obs` |
(matrix of) observed summary statistics. |

`param` |
matrix of simulated model parameter values. |

`sumstats` |
matrix of simulated summary statistics. |

`obspar` |
optional observed parameters (for use to assess simulation performance). |

`abcmethod` |
a function to perform ABC inference, e.g. the |

`saprop` |
a proportion, denoting the proportion of simulated datasets with which to perform semi-automatic ABC regression. |

`abcprop` |
a proportion, denoting the proportion of simulated datasets with which to perform ABC using |

`overlap` |
a boolean value indicating whether the simulated datasets specified by |

`satr` |
a list of functions indicating transformations of the summary statistics |

`plot` |
When plot==TRUE, a plot of parameter values against fitted values is produced for each parameter as a side-effect. This is most useful when the number of parameters is reasonably small. |

`verbose` |
a boolean value indicating whether informative statements should be printed to screen. |

`do.err` |
a boolean value indicating whether the simulation error should be returned. Note: if |

`final.dens` |
a boolean value indicating whether the posterior sample should be returned. |

`errfn` |
an error function to assess ABC inference performance. |

`...` |
any other optional arguments to the ABC inference procedure (e.g. arguments to the |

### Details

This function is essentially a wrapper for `saABC`

. See the details section of `saABC`

for more details on the implementation. The argument `satr`

can be almost anything sensible in `function`

form, see Examples section for example specifications.

### Value

A list with the following components:

`err` |
simulation error (if |

`post.sample` |
an array of dimension |

`sainfo` |
A list with the following information about the semi-automatic ABC run: |

### Warning

The argument `satr`

must be supplied with valid functions. Whilst there are checks, these are minimal, since doing sophisticated checks is quite difficult.

### Author(s)

Matt Nunes and Dennis Prangle

### References

Blum, M. G. B, Nunes, M. A., Prangle, D. and Sisson, S. A. (2013) A
comparative review of dimension reduction methods in approximate
Bayesian computation. *Stat. Sci.* **28**, Issue 2, 189–208.

Fearnhead, P. and Prangle, D. (2012) Constructing summary statistics for approximate Bayesian computation:
semi-automatic approximate Bayesian
computation. *J. R. Stat. Soc. B* **74**, Part 3, 1–28.

Nunes, M. A. and Prangle, D. (2016) abctools: an R package for tuning
approximate Bayesian computation analyses. *The R Journal*
**7**, Issue 2, 189–205.

### See Also

### Examples

```
## Not run:
data(coal)
data(coalobs)
param<-coal[,2]
simstats<-coal[,4:6]
# use matrix below just in case to preserve dimensions.
obsstats<-matrix(coalobs[1,4:6],nrow=1)
obsparam<-matrix(coalobs[1,1])
# perform semi-automatic ABC with summary statistics defined by
# X, X^2,X^3,X^4:
# other alternative specifications for this could be:
# list(function(x){ cbind(x,x^2,x^3,x^4) })
# list(as.function(alist(x=,cbind(x,x^2,x^3)))) etc
tmp<-semiauto.abc(obsstats, param, simstats,tol=.01,method="rejection",
satr=list(function(x){outer(x,Y=1:4,"^")}))
tmp$sa.info
# both these functions may be problematic:
tmp<-semiauto.abc(obsstats, param, simstats,tol=.01,method="rejection",
satr=list(unique,sum))
## End(Not run)
```

*abctools*version 1.1.7 Index]