anchor_stability {AnchorRegression} | R Documentation |

## anchor_stability

### Description

Perform an Anchor Stability Analysis as described in Rothenhäusler et al.2020

### Usage

```
anchor_stability(
x,
anchor,
target_variable,
lambda = 0,
alpha = 0.05,
p_procedure = "naive"
)
```

### Arguments

`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 |

### Value

A dataframe containing the stability values for each coefficient

### Examples

```
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")
```

[Package

*AnchorRegression*version 0.1.3 Index]