post_stratification {autoMrP}  R Documentation 
Apply poststratification to classifiers.
post_stratification( y, L1.x, L2.x, L2.unit, L2.reg, best.subset.opt, lasso.opt, lasso.L2.x, pca.opt, gb.opt, svm.opt, svm.L2.reg, svm.L2.unit, svm.L2.x, mrp.include, n.minobsinnode, L2.unit.include, L2.reg.include, kernel, mrp.L2.x, data, ebma.fold, census, verbose )
y 
Outcome variable. A character vector containing the column names of
the outcome variable. A character scalar containing the column name of
the outcome variable in 
L1.x 
Individuallevel covariates. A character vector containing the
column names of the individuallevel variables in 
L2.x 
Contextlevel covariates. A character vector containing the
column names of the contextlevel variables in 
L2.unit 
Geographic unit. A character scalar containing the column
name of the geographic unit in 
L2.reg 
Geographic region. A character scalar containing the column
name of the geographic region in 
best.subset.opt 
Optimal tuning parameters from best subset selection
classifier. A list returned by 
lasso.opt 
Optimal tuning parameters from lasso classifier A list
returned by 
lasso.L2.x 
Lasso contextlevel covariates. A character vector
containing the column names of the contextlevel variables in

pca.opt 
Optimal tuning parameters from best subset selection with
principal components classifier A list returned by 
gb.opt 
Optimal tuning parameters from gradient tree boosting
classifier A list returned by 
svm.opt 
Optimal tuning parameters from support vector machine
classifier A list returned by 
svm.L2.reg 
SVM L2.reg. A logical argument indicating whether

svm.L2.unit 
SVM L2.unit. A logical argument indicating whether

svm.L2.x 
SVM contextlevel covariates. A character vector containing
the column names of the contextlevel variables in 
mrp.include 
Whether to run MRP classifier. A logical argument
indicating whether the standard MRP classifier should be used for
predicting outcome 
n.minobsinnode 
GB minimum number of observations in the terminal
nodes. An integervalued scalar specifying the minimum number of
observations that each terminal node of the trees must contain. Passed from

L2.unit.include 
GB L2.unit. A logical argument indicating whether

L2.reg.include 
A logical argument indicating whether 
kernel 
SVM kernel. A charactervalued scalar specifying the kernel to
be used by SVM. The possible values are 
mrp.L2.x 
MRP contextlevel covariates. A character vector containing
the column names of the contextlevel variables in 
data 
A data.frame containing the survey data used in classifier training. 
ebma.fold 
A data.frame containing the data not used in classifier training. 
census 
Census data. A 
verbose 
Verbose output. A logical argument indicating whether or not
verbose output should be printed. Default is 