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