Description Usage Arguments Details Value Author(s) Examples

The function estimates a linear model by using Ordinary-Least-Squares regression. OLS-coefficients and common summary statistics of the estimation are provided.

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`X` |
A data matrix with a column of 1 for each observation and one column for each independent variable must be specified. |

`Y` |
A data matrix with a column for the dependent variable must be specified. |

`data` |
The name of the used data-frame must be specified, so that the names of the variables can be extracted. |

Given the matrix of the dependent variabe Y and the matrix of the independent variables X, the function ols returns an estimate of the respective OLS-coefficients for each independent variable and the estimate of the intercept for the dependent variable. Additionally, ols also returns common summary statistics for the model.

The output is a k+1x6 matrix with the name of the estimated coefficients, estimate, standard error, t-value and p-value; and a summary of the residuals, residual standard error, degrees of freedom, multiple-R-squared and F-statistics

Johannes Besch, [email protected], Marco Radojevic [email protected]

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