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autoMrP 1.0.6

• implements Deep MrP by Gopelrud as presented in https://doi.org/10.1017/S0003055423000035
• Set argument deep.mrp = TRUE to include Deep MrP in the ensemble

autoMrP 1.0.5

• drops missing values on y, L1.x, L2.x, L2.unit, L2.reg. Missing values on the DV would previously lead to errors in SVM
• works with continuous DV.

autoMrP 0.93

• block sampling in bootstrapping instead of state-stratified sampling

autoMrP 0.91

• bootstrapping returns GB prediction
• predictions do not fail if census data contains more factor levels than training data for SVM and Lasso
• svm post-stratification uses the user-specified formula instead of all information
• lasso post-stratification uses correct user-specified context level variables if L2.x and lasso.L2.x differ
• parallel processing loops are replicable now

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.