anchor_stability {AnchorRegression} | R Documentation |
Perform an Anchor Stability Analysis as described in Rothenhäusler et al.2020
anchor_stability( x, anchor, target_variable, lambda = 0, alpha = 0.05, p_procedure = "naive" )
x |
is a dataframe containing the matrix x containing the independent variables |
anchor |
is a dataframe containing the matrix anchor containing the anchor variable |
target_variable |
is the target variable name contained in the x dataframe |
lambda |
indicates the lambda that is used in the Anchor Regression. 'CV' is used if it should be estimated by cross validation on the full subset. |
alpha |
significance level for test decision on coefficient significance |
p_procedure |
procedure to estimate stability. Option 1: naive - stable if effect is non-zero in all cases; Option 2: post-lasso - post selection inference using SelectiveInference package |
A dataframe containing the stability values for each coefficient
x <- as.data.frame(matrix(data = rnorm(1000),nrow = 100,ncol = 10)) anchor <- as.data.frame(matrix(data = rnorm(200),nrow = 100,ncol = 2)) colnames(anchor) <- c('X1','X2') gamma <- 2 target_variable <- 'V2' anchor_stability(x, anchor, target_variable, lambda, alpha=0.05, p_procedure = "naive")