Fit Two Innate Rates Model (TIRM)

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Description

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

Usage

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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

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

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

Author(s)

Matthew W. Pennell

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

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## 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