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capwire (version 1.1.4)

fitTirm: Fit Two Innate Rates Model (TIRM)

Description

Fits the Two Innate Rates Model (TIRM) to count data to obtain the MLE for population size

Usage

fitTirm(data, max.pop)

Arguments

data
A two-column data frame with the first column specifiying the capture class (i.e. individuals in class i were caught i times) and the second column specifying the number of individuals in each class
max.pop
The maximum population size

Value

model
The model specified
likelihood
The likelihood of the model
ml.pop.size
The maximum likelihood estimate for population size
ml.na
The maximum likelihood estimate for the number of individuals in class A
ml.nb
The maximum likelihood estimate for the number of individuals in class B
alpha
The ratio of the rates of captures between class A and class B individuals
cap.ind
The mean number of captures per individual
sampled.ind
The total number of individuals in the sample
sample.size
Total number of samples in the data set
max.pop
The maximum population size specified by max.pop

Details

The TIRM model fit by this function assumes that individuals can be assigned to two classes. Class A represent the frequently captured individuals. Class B represents the infrequently captured individuals.

The value is specified for max.pop is not likely to matter as long as it is much greater than the maximum likelihood estimate for population size.

Note that if the data contains only singletons, the data is not informative and the maximum likelihood estimate for population size will be equal to max.pop

References

Miller C. R., P. Joyce and L.P. Waits. 2005. A new method for estimating the size of small populations from genetic mark-recapture data. Molecular Ecology 14:1991-2005.

See Also

simTirm

Examples

Run this code
## Simulate data under Two Innate Rates Model

data <- simTirm(na=20, nb=15, alpha=4, s=150)

## Fit Two Innate Rates Model to Data

res <- fitTirm(data=data, max.pop=200)

res

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