Natural feeling domain-specific language for building structural equation models in R for estimation by covariance-based methods (like LISREL/Lavaan) or partial least squares (like SmartPLS)
58
stars
19
forks
source link
predict_pls: Subscript `endogenous_items` must be a simple vector, not a matrix #333
Hi, I'm trying to apply predict_pls, but I get this error:
Parallel encountered this ERROR:
Can't subset columns with endogenous_items.
✖ Subscript endogenous_items must be a simple vector, not a matrix.Error in parallel::stopCluster(cl) : object 'cl' not found
It's strange that I encounter an error with the parallel process since I want to use k-fold cross-validation. I tried specifying noFolds = 10 and cores=NULL, but I still get the same error. Here are my codes.
###### Measurement model
mm_em <- constructs(composite("VVLT", multi_items("vvlt", 1:4)),
composite("VEOU", multi_items("veou", 1:2)),
composite("VRA", multi_items("vra", 1:2)),
composite("VINT", multi_items("vint", 1:3)))
###### Structural model
inner_model_em <- relationships(paths(from = c("VVLT", "VEOU", "VRA"), to = "VINT"))
###### Estimate the model
em <- estimate_pls(data = data,
measurement_model = mm_em,
structural_model = inner_model_em,
inner_weights = path_weighting)
###### PLSpredict
pred <- predict_pls(model = em, technique = predict_DA, noFolds = 10, reps = 10, cores = NULL)
Hi, I'm trying to apply
predict_pls
, but I get this error:It's strange that I encounter an error with the parallel process since I want to use k-fold cross-validation. I tried specifying
noFolds = 10
andcores=NULL
, but I still get the same error. Here are my codes.Thanks a lot!