process.data: Process data for fitting distance sampling detection function
In mrds: Mark-Recapture Distance Sampling

process.data

R Documentation

Process data for fitting distance sampling detection function

Description

Sets up dataframe and does some basic error checking. Adds needed fields to dataframe and to meta.data.

Usage

process.data(data, meta.data = list(), check = TRUE)

Arguments

`data`	dataframe object
`meta.data`	meta.data options; see `ddf` for a description
`check`	if `TRUE` check data for errors in the mrds structure; for `method="ds" check=FALSE`

Details

The function does a number of error checking tasks, creating fields and adding to meta.data including:

1) If check=TRUE, check to make sure the record structure is okay for mrds data. The number of primary records (observer=1) must equal the number of secondary records (observer=2). Also, a field in the dataframe is created timesseen which counts the number of times an object was detected 0,1,2; if timesseen=0 then the record is tossed from the analysis. Also if there are differences in the data (distance, size, covariates) for observer 1 and 2 a warning is issued that the analysis may fail. The code assumes these values are the same for both observers.

2) Based on the presence of fields distbegin and distend, a determination is made of whether the data analysis should be based on binned distances and a field binned is created, which is TRUE if the distance for the observation is binned. By assigning for each observation this allows an analysis of a mixture of binned and unbinned distances.

4) Data are restricted such that distances are not greater than width and not less than left if those values are specified in meta.data. If they are not specified then left defaults to 0 and width defaults to the largest distance measurement.

5) Determine if an integration range (int.begin and int.end has been specified for the observations. If it has, add the structure to meta.data. The integration range is typically used for aerial surveys in which the altitude varies such that the strip width (left to width) changes with a change in altitude.

6) Fields defined as factors are cleaned up such that any unused levels are eliminated.

7) If the restrictions placed on the data, eliminated all of the data, the function stops with an error message