Description Usage Arguments Details Value Author(s) See Also Examples

This function creates a matrix of covariates or design matrix appropriate for BaSTA from raw individual level covariate data. The function identifies categorical and continuous covariates and organizes them accordingly.

1 | ```
MakeCovMat(x, data)
``` |

`x ` |
A character string vector or a numerical vector indicating the columns to be included or an object of class |

`data ` |
A data frame of n rows (n = number of individuals in dataset) and nz columns (number of general covariates) including categorical covariates as factors (e.g. sex with individual labels "f","m", location, etc.) and/or continuous individual covariates (e.g. weight at birth, general weather conditions at each location, etc.). |

The `x`

argument can be of class `character`

, `numeric`

or `formula`

as long as the elements described correspond to the column names in the `data`

data frame.
The data frame specified in argument `data`

needs to explicitly differentiate between categorical and numerical variables. The elements in the column of a categorical variable must be coerced to be `factors`

.

The function returns a new covariate matrix to be collated to a matrix that includes a column for individual ID, a column for time of birth, and a column for times of death, plus the full recapture matrix.

Owen R. Jones [email protected] and Fernando Colchero [email protected]

1 2 3 4 5 | ```
## Simulated sex and weight data for 5 individuals:
sex <- sample(c("f", "m"), 5, replace = TRUE)
weight <- rnorm(5, mean = 10, sd = 1)
raw.mat <- data.frame(sex, weight)
new.mat <- MakeCovMat(~sex + weight, data = raw.mat)
``` |

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```

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