strandCet (version 1.0)

Si.mod: Siler model.

Description

Fit a 5-parameters Competing-Risk Siler model for Animal Mortality.

Usage

Si.mod(data, par = c(-0.15, 1.1, 0.15, 0.005, 0.15), rm = 0,
  method = "Nelder-Mead", control = list(fnscale = -1, maxit = 10000))

Arguments

data

Data frame with age clases and frequency of occurrence (see Details).

par

Initial values for the Siler parameters to be optimized over.

rm

The number of age classes that want to be removed from optimization (see Details).

method

The method to be used: "Nelder-Mead", "BFGS", "CG", "L-BFGS-B", "SANN" or "Brent" (see optim).

control

A list of control parameters (see optim).

Details

The data used must be a data frame whose first column is a vector of the estimated ages of the animals found dead and the second the frequency of occurrence of those ages.

All age classes are used for adjustment, in case of whish to remove any of the first age classes due to bias in the sample, indicate it with the parameter "rm" and these will be removed starting from the first age class.

References

Siler, W. (1979). A Competing-Risk Model for Animal Mortality. Ecology 60, 750<U+2013>757.

Siler, W. (1983). Parameters of mortality in human populations with widely varying life spans. Stat. Med. 2, 373<U+2013>380.

Nocedal, J. and Wright, S. J. (1999). Numerical Optimization. Springer.

See Also

optim

Examples

# NOT RUN {
Si.mod(data = cetaceans, rm = 2,
       par = c(0.3159462,  0.1860541, -1.2802880,  1.1733226,  0.0170314))

Si.mod(data = cetaceans, rm = 1,
       par = c(0.3159462,  0.1860541, -1.2802880,  1.1733226,  0.0170314))

Si.mod(data = cetaceans, rm = 0,
       par = c(0.3159462,  0.1860541, -1.2802880,  1.1733226,  0.0170314))

# }