lassoSelect {lvnet} | R Documentation |
Update lvnatLasso results to select a different model
Description
This function can be used to select a model using any fit index
Usage
lassoSelect(object, select, minimize = TRUE, refit = TRUE, lassoTol = 1e-04)
Arguments
object |
An |
select |
A raw R expression using names used in the |
minimize |
Logical. Minimize or maximize? |
refit |
Logical. Should the new best model be refitted. |
lassoTol |
Tolerance for absolute values to be treated as zero in counting parameters. |
Author(s)
Sacha Epskamp <mail@sachaepskamp.com>
Examples
## Not run:
# Load dataset:
library("lavaan")
data(HolzingerSwineford1939)
Data <- HolzingerSwineford1939[,7:15]
# Measurement model:
Lambda <- matrix(0, 9, 3)
Lambda[1:3,1] <- NA
Lambda[4:6,2] <- NA
Lambda[7:9,3] <- NA
# Search best fitting omega_theta:
res <- lvnetLasso(Data, "omega_theta", lambda = Lambda)
res$best
summary(res)
# Update to use EBIC:
resEBIC <- lassoSelect(res, ebic)
summary(resEBIC)
# Update to use minimal fitting model with RMSEA < 0.05:
resMinimal <- lassoSelect(res, df * (rmsea < 0.05), minimize = FALSE)
summary(resMinimal)
## End(Not run)
[Package lvnet version 0.3.5 Index]