Comments (6)
from fixedeffectmodels.jl.
Thanks for the quick response Matthieu. I went to the master branch using Pkg.checkout("FixedEffectModels")
but I'm still getting the same segfault. I should perhaps add that memory use before the segfault is not particularly high...
from fixedeffectmodels.jl.
Seemed to have indeed been a memory issue.
from fixedeffectmodels.jl.
Ok. Out of curiosity could you tell me the size of your memory compared to the size of the dataset?
from fixedeffectmodels.jl.
The dataframe was about 20gb (according to Base.summarysize()
); total memory on the machine was 64gb. Not sure it is/was really related to FixedEffectModels, actually. These days I tend to trim down my dataframes before running regressions, and that works ok for me.
from fixedeffectmodels.jl.
Ok thanks!
from fixedeffectmodels.jl.
Related Issues (20)
- MethodError: no method matching fe(::CategoricalValue{String15, UInt32}) HOT 1
- Implement StatsAPI.fit() HOT 1
- Generate confidence intervals for `predict` HOT 1
- Ignore rows with `Inf`s? HOT 3
- error in using gpu? HOT 3
- Feature request: GPU support in MacOS HOT 2
- Drop regressors that are collinear with the fixed effects (depending on tolerance for partialling-out)
- Get " run `reg` with the option save = :residuals" despite doing exactly that HOT 3
- How can I get the dof? HOT 2
- Degrees of freedom always 1 HOT 1
- Demeaning HOT 3
- Print name of dependent variable in FixedEffectModel results display? HOT 1
- tolerance in `invsym!` HOT 1
- Next release please! For Stata front-end HOT 4
- `predict` for fixed effects HOT 4
- Feature request: Saving an object of type `FixedEffectModel` HOT 1
- Using r2 as a regression name conflicts with r2 (r-squared?) HOT 1
- Wrong results in a large data set with one set of FE HOT 51
- `predict` doesn't work for FE-only models
- Poor multithreading performance with very small FE groups HOT 3
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from fixedeffectmodels.jl.