Hi I'm having a problem with model.frame, encapsulated in this example:
y1 <- matrix(c(3,1,0,1,0,1,1,0,0,0,1,0,0,0,1,1,0,1,1,1),
nrow = 5, byrow = TRUE)
y1 <- as.data.frame(y1)
rownames(y1) <- paste("site", 1:5, sep = "")
colnames(y1) <- paste("spp", 1:4, sep = "")
y1
model.frame(~ y1)
Error in model.frame(formula, rownames, variables, varnames, extras,
extranames, :
invalid variable type
temp <- as.matrix(y1)
model.frame(~ temp)
temp.spp1 temp.spp2 temp.spp3 temp.spp4
1 3 1 0 1
2 0 1 1 0
3 0 0 1 0
4 0 0 1 1
5 0 1 1 1
Ideally the above wouldn't have names like temp.var1, temp.var2, but one
could deal with that later.
I have tracked down the source of the error message to line 1330 in
model.c - here I'm stumped as I don't know any C, but it looks as if the
code is looping over the variables in the formula and checking of they
are the right "type". So a matrix of variables gets through, but a
data.frame doesn't.
It would be good if model.frame could cope with data.frames in formulae,
but seeing as I am incapable of providing a patch, is there a way around
this problem?
Below is the head of the function I am currently using, including the
function for parsing the formula - borrowed and hacked from
ordiParseFormula() in package vegan.
I can work out the class of the rhs of the forumla. Is there a way to
create a suitable environment for the data argument of parseFormula()
such that it contains the rhs dataframe coerced to a matrix, which then
should get through model.frame.default without error? How would I go
about manipulating/creating such an environment? Any other ideas?
Thanks in advance
Gav
coca.formula <- function(formula, method = c("predictive", "symmetric"),
reg.method = c("simpls", "eigen"), weights = NULL,
n.axes = NULL, symmetric = FALSE, data)
{
parseFormula <- function (formula, data)
{
browser()
Terms <- terms(formula, "Condition", data = data)
flapart <- fla <- formula <- formula(Terms, width.cutoff = 500)
specdata <- formula[[2]]
X <- eval(specdata, data, parent.frame())
X <- as.matrix(X)
formula[[2]] <- NULL
if (formula[[2]] == "1" || formula[[2]] == "0")
Y <- NULL
else {
mf <- model.frame(formula, data, na.action = na.fail)
Y <- model.matrix(formula, mf)
if (any(colnames(Y) == "(Intercept)")) {
xint <- which(colnames(Y) == "(Intercept)")
Y <- Y[, -xint, drop = FALSE]
}
}
list(X = X, Y = Y)
}
if (missing(data))
data <- parent.frame()
#browser()
dat <- parseFormula(formula, data)
--
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Gavin Simpson [T] +44 (0)20 7679 5522
ENSIS Research Fellow [F] +44 (0)20 7679 7565
ENSIS Ltd. & ECRC [E] gavin.simpsonATNOSPAMucl.ac.uk
UCL Department of Geography [W] http://www.ucl.ac.uk/~ucfagls/cv/
26 Bedford Way [W] http://www.ucl.ac.uk/~ucfagls/
London. WC1H 0AP.
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