| Detailed description |
Hi,
I try to fit a model with a 34.000 level factor input interacting with a 2-level factor.
The data look like this:
> str(z)
'data.frame': 407028 obs. of 5 variables:
$ factorB : Factor w/ 2 levels "1","3": 1 1 1 1 1 1 1 1 1 1 ...
$ replicate: Factor w/ 13 levels "1","10","11",..: 1 1 1 1 1 1 1 1 1 1 ...
$ factorA : Factor w/ 33919 levels "1","2","3","4",..: 2253 13953 16821 15272 29539 2215 2217 13458 10491 25005 ...
$ value : int 37 34 0 0 0 0 0 0 0 0 ...
$ exposure : int 575366 575366 575366 575366 575366 575366 575366 575366 575366 575366 ...
This is the result when fitting the model:
> zm <- glm4(sqrt(value / exposure) ~ factorA + factorA:factorB - 1,
+ data=z,
+ family=gaussian(link="identity"),
+ sparse=TRUE);
*** caught segfault ***
address 0x2b7308f8f000, cause 'memory not mapped'
Traceback:
1: .Call(Csparse_submatrix, x, ii, NULL)
2: subCsp_rows(x, i, drop = drop)
3: x[i = i, , drop = TRUE]
4: x[i = i, , drop = TRUE]
5: eval(expr, envir, enclos)
6: eval(call, sys.frame(sys.parent()))
7: callGeneric(x, i = i, , drop = TRUE)
8: Y[rep(seq_len(ny), each = nx), ]
9: Y[rep(seq_len(ny), each = nx), ]
10: sparse2int(sparseInt.r(rList[-m], do.names = do.names), rList[[m]], do.names = do.names)
11: F(sparse2int(sparseInt.r(rList[-m], do.names = do.names), rList[[m]], do.names = do.names))
12: sparseInt.r(lapply(nmSplits, getR), do.names = TRUE, forceSparse = TRUE)
13: model.spmatrix(t, data, transpose = transpose, drop.unused.levels = drop.unused.levels, row.names = row.names)
14: sparse.model.matrix(object, data = data, contrasts.arg = contrasts.arg, drop.unused.levels = drop.unused.levels, xlev = xlev, ...)
15: model.Matrix(formula, mf, sparse = sparse, drop.unused.levels = drop.unused.levels)
16: .class1(object)
17: as(model.Matrix(formula, mf, sparse = sparse, drop.unused.levels = drop.unused.levels), "predModule")
18: initialize(value, ...)
19: initialize(value, ...)
20: new("glpModel", call = call, resp = mkRespMod(mf, family), pred = as(model.Matrix(formula, mf, sparse = sparse, drop.unused.levels = drop.unused.levels), "predModule"))
21: glm4(sqrt(value/exposure) ~ factorA + factorA:factorB - 1, data = z, family = gaussian(link = "identity"), sparse = TRUE)
I would appreciate your assistance in this!
Regards,
Philip
> sessionInfo()
R version 2.12.2 (2011-02-25)
Platform: x86_64-unknown-linux-gnu (64-bit)
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=C LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] MatrixModels_0.2-1 Matrix_0.999375-46 lattice_0.19-17
loaded via a namespace (and not attached):
[1] grid_2.12.2
|
|
