Description Usage Arguments Value Author(s) References Examples
Construct a transfer object to simulate the number of glass fragments recovered given the conditions set by the user.
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N |
Simulation size |
d |
The breaker's distance from the window |
deffect |
Distance effect. |
lambda |
The average number of glass fragments transferred to the breaker's clothing. |
Q |
Proportion of high persistence fragments. |
l0 |
Lower bound on the percentage of fragments lost in the first hour |
u0 |
Upper bound on the percentage of fragments lost in the first hour |
lstar0 |
Lower bound on the percentage of high persistence fragments lost in the first hour |
ustar0 |
Upper bound on the percentage of high persistence fragments lost in the first hour |
lj |
Lower bound on the percentage of fragments lost in the j'th hour |
uj |
Upper bound on the percentage of fragments lost in the j'th hour |
lstarj |
Lower bound on the percentage of high persistence fragments lost in the j'th hour |
ustarj |
Upper bound on the percentage of high persistence fragments lost in the j'th hour |
lR |
Lower bound on the percentage of fragments expected to be detected in the lab |
uR |
Upper bound on the percentage of fragments expected to be detected in the lab |
lt |
Lower bound on time between commission of crime and apprehension of suspect |
ut |
Upper bound on time between commission of crime and apprehension of suspect |
r |
Probability r in ti ~ NegBinom(t, r) |
timeDist |
the distribution for the random amount of time between the commission of
the crime and the apprehension of the suspect. There are three choices |
loop |
if |
a list
containing:
The simulated values of recovered glass fragments
Input parameters
The returned object has S3 class types tfer and transfer for backwards compatibility
James Curran and TingYu Huang
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 probabilities (default)
plot(y)
plot(y)
## barplot of transfer frequencies
plot(y, ptype = "f")
## histogram
plot(y, ptype = "h")
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