Regularized tessellation density estimation with bootstrap aggregation and complexity penalization

► We suggest an ensemble tessellation method for non-parametric density estimation. ► We introduce a model selection procedure with complexity penalization. ► Information-theoretic model selection yields a tessellation estimator with good bias/variance properties. ► Simulation studies illustrate the effectiveness of the estimator in one and two dimensions.