Diagnosis of collinearity in X

`cond.index(formula, data, ...)`

formula

formula of the form ‘`groups ~ x1 + x2 + ...`

’

data

data frame (or matrix) containing the explanatory variables

...

further arguments to be passed to `lm`

A vector of the condition indices.

Collinearities can inflate the variance of the estimated regression coefficients and numerical stability. The condition indices are calculated by the eigenvalues of the crossproduct matrix of the scaled but uncentered explanatory variables. Indices > 30 may indicate collinearity.

Belsley, D. , Kuh, E. and Welsch, R. E. (1979), *Regression Diagnostics: Identifying Influential Data and Sources of Collinearity*,
John Wiley (New York)

# NOT RUN { data(Boston) condition_medv <- cond.index(medv ~ ., data = Boston) condition_medv # }