Statistical interpretation of forensic glass transfer (Simulation of the probability distribution of recovered glass fragments).

Package: | tfer |

Type: | Package |

Version: | 1.1 |

Date: | 2010-11-07 |

License: | GPL-2 |

LazyLoad: | yes |

Depends: | methods |

The `tfer`

package provides functions for simulating the number of
recovered glass fragments given the conditions set by the user on
factors affecting the transfer, persistence and recovery of glass
fragments. A large simulation size will provide precise estimates of
transfer probabilities to be used in the Bayesian interpretation of
forensic glass evidence.

The `transfer`

constructor function creates an object of class
`transfer`

consisting of a list of simulated number of recovered
glass fragments and the input parameters set by the user. This function
is based on the full graphical model in Curran *et al.* (1998). The
user can specify arguments for simulation size, distance, transfer,
persistence and recovery properties.

The `values`

function extracts the simulated random variates from a
`transfer`

object. `para`

returns the input parameters and
user-specified arguments as a numeric vector. `parameters`

is an
alternative way of displaying the input parameters and arguments. The
initial information specified by the user are concatenated and displayed
as a string. Users may find this more informative than `para`

as it
displays what each parameter denotes.

`tprob`

returns the transfer probabilities for each
unique value of the simulated random variates. If the user is only
interested in the probabilities of recovering a certain number of
fragments, this can be specified as the second argument of `tprob`

.

`summary`

provides summary statistics of `transfer`

objects
and returns a list of input parameters, five-number summary and
probabilities of transfer.

The user has three plotting options for producing a graphical view of a
`transfer`

object. The plot type can be specified as (0 = barplot
of probabilities, 1 = barplot of frequencies or 2 = histogram).
A barplot of probabilities is set as the default.

James Curran and TingYu Huang

Maintainer: TingYu Huang <thua041@aucklanduni.ac.nz>

Curran, J. M., Hicks, T. N. & Buckleton, J. S. (2000). *Forensic
interpretation of glass evidence*. Boca Raton, FL: CRC Press.

Curran, J. M., Triggs, C. M., Buckleton, J. S., Walsh, K. A. J. &
Hicks, T. N. (January, 1998). Assessing transfer probabilities in a
Bayesian interpretation of forensic glass evidence. *Science &
Justice*, *38*(1), 15-21.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | ```
library(tfer)
## create a transfer object using default arguments
y = transfer()
## probability table
probs = tprob(y)
## extract the probabilities of recovering 8 to 15
## glass fragments given the user-specified arguments
tprob(y, 8:15)
## produce a summary table for a transfer object
summary(y)
## barplot of transfer probabilities (default)
plot(y, ptype = 0)
plot(y)
## barplot of transfer frequencies
plot(y, ptype = 1)
## histogram
plot(y, ptype = 2)
``` |

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