ivar: Expand Individual-varying covariates in models
In mra: Mark-Recapture Analysis

Description Usage Arguments Value Author(s) See Also Examples

Expands a vector of individual-varying values into a 2-d matrix of the appropriate size for use in MRA model formulas.

1	ivar(x, ns=attr(x,"ns"), drop.levels=attr(x,"drop.levels"))

`x`	The vector of individual varying values to expand. This can be a factor (see `as.factor`). It is assumed that `length(x)` = number of individuals. If not, an error will occur in whatever routine called this function (e.g., `F.3d.model.matrix`).
`ns`	Number of sampling occasions. Default is to use the 'ns' attribute of `x`. If `ns` is not specified or is not an attribute of `x`, an error is thrown.
`drop.levels`	A vector of integers specifying which levels of a factor to drop. Only applicable if `x` is a factor. By default, the the 'drop.levels' attribute of `x` is used. If `x` does not have a 'drop.levels' attribute, the first level of the factor is dropped. `drop.levels=length(levels(x))` does the SAS thing and drops the last level of a factor. Specifying multiple levels to drop is acceptable. E.g., `drop.levels=c(1,2,7)` drops the 1st, 2nd, and 7th levels of the factor, whatever they are. First level of a factor is first element of `levels(x)`. Second level of a factor is second element of `levels(x)`, and so on. Setting `drop.levels` to 0, a negative number, or a number greater than the number of levels will not drop any levels (this is so-called cell mean coding). Keep in mind presence of the intercept.

A 2-d matrix of size length(x) x ns suitable for passing to the Fortran DLL of MRA for estimation. Values within rows are constant, values across rows vary according to x. If x is a factor, this matrix contains 0-1 indicator functions necessary to fit the factor.

If x is a factor, attributes of the returned matrix are "levels" = levels of the factor and "contr" = contrasts used in the coding (always contr.treatment). For other contrast coding of factors, make your own 2-d matrix with a call to the appropriate function (like contr.poly).

Trent McDonald, WEST-INC, tmcdonald@west-inc.com

F.cjs.estim, tvar

nan <- 30
ns <- 5
age <- as.factor(sample( c("J","S1","S2","Adult"), size=nan, replace=TRUE ))
attr(age,"ns") <- ns

# Note that levels get reordered (by R default, alphabetically)
attr(age,"drop.levels") <- (1:length(levels(age)))[ levels(age) == "J" ]

age.mat <- ivar(age)  # level J is the reference
age.mat <- ivar(age, drop=4) # level S2 is the reference

# Look at 3-D matrix produced when called with a factor.
dim(age.mat) <- c(nan,ns,length(levels(age))-1)
print(age.mat)  # each page is the 2-d matrix used in the fit.
print(age.mat[1,,])

age.mat <- ivar(age, drop=c(3,4))  # level S1 and S2 are combined and are the reference

# compare above to 
ivar( c(1,1,2,2,3,3), 5 )