statsmodels.stats.multivariate.confint_mvmean

statsmodels.stats.multivariate.confint_mvmean(data, lin_transf=None, alpha=0.5, simult=False)

Confidence interval for linear transformation of a multivariate mean

Either pointwise or simultaneous confidence intervals are returned.

Parameters:

dataarray_like

data with observations in rows and variables in columns

lin_transfarray_like or None

The linear transformation or contrast matrix for transforming the vector of means. If this is None, then the identity matrix is used which specifies the means themselves.

alphafloat in (0, 1)

confidence level for the confidence interval, commonly used is alpha=0.05.

simultbool

If simult is False (default), then the pointwise confidence interval is returned. Otherwise, a simultaneous confidence interval is returned. Warning: additional simultaneous confidence intervals might be added and the default for those might change.

Returns:

lowndarray

lower confidence bound on the linear transformed

uppndarray

upper confidence bound on the linear transformed

valuesndarray

mean or their linear transformation, center of the confidence region

Notes

Pointwise confidence interval is based on Johnson and Wichern equation (5-21) page 224.

Simultaneous confidence interval is based on Johnson and Wichern Result 5.3 page 225. This looks like Sheffe simultaneous confidence intervals.

Bonferroni corrected simultaneous confidence interval might be added in future

References

Johnson, Richard A., and Dean W. Wichern. 2007. Applied Multivariate Statistical Analysis. 6th ed. Upper Saddle River, N.J: Pearson Prentice Hall.