# ddf.rem: Mark-Recapture Distance Sampling (MRDS) Removal - PI In mrds: Mark-Recapture Distance Sampling

 ddf.rem R Documentation

## Mark-Recapture Distance Sampling (MRDS) Removal - PI

### Description

Mark-Recapture Distance Sampling (MRDS) Analysis of Removal Observer Configuration and Point Independence

### Usage

```## S3 method for class 'rem'
ddf(dsmodel, mrmodel, data, meta.data = list(), control = list(), call = "")
```

### Arguments

 `dsmodel` distance sampling model specification; model list with key function and scale formula if any `mrmodel` mark-recapture model specification; model list with formula and link `data` analysis dataframe `meta.data` list containing settings controlling data structure `control` list containing settings controlling model fitting `call` original function call used to call `ddf`

### Details

MRDS analysis based on point independence involves two separate and independent analyses of the mark-recapture data and the distance sampling data. For the removal observer configuration, the mark-recapture data are analysed with a call to `ddf.rem.fi` (see Laake and Borchers 2004) to fit conditional distance sampling detection functions to estimate p(0), detection probability at distance zero for the primary observer based on independence at zero (eq 6.22 in Laake and Borchers 2004). Independently, the distance data, the observations from the primary observer, are used to fit a conventional distance sampling (CDS) (likelihood eq 6.6) or multi-covariate distance sampling (MCDS) (likelihood eq 6.14) model for the detection function, g(y), such that g(0)=1. The detection function for the primary observer is then created as p(y)=p(0)*g(y) (eq 6.28 of Laake and Borchers 2004) from which predictions are made. `ddf.rem` is not called directly by the user and is called from `ddf` with `method="rem"`.

For a complete description of each of the calling arguments, see `ddf`. The argument `data` is the dataframe specified by the argument `data` in `ddf`. The arguments `dsmodel`, `mrmodel`, `control` and `meta.data` are defined the same as in `ddf`.

### Value

result: an rem model object which is composed of rem.fi and ds model objects

Jeff Laake

### References

Laake, J.L. and D.L. Borchers. 2004. Methods for incomplete detection at distance zero. In: Advanced Distance Sampling, eds. S.T. Buckland, D.R.Anderson, K.P. Burnham, J.L. Laake, D.L. Borchers, and L. Thomas. Oxford University Press.

`ddf.rem.fi`, `ddf.ds`