Department of Economics and Business Economics

Local Linear Density Estimation for Filtered Survival Data with Bias Correction

Research output: Working paperResearch

  • Carsten Tanggaard
  • Jens Perch Nielsen, Cass Business School, London, United Kingdom
  • M.C. Jones, The Open University, Milton Keynes, United Kingdom
  • School of Economics and Management
A class of local linear kernel density estimators based on weighted least squares kernel estimation is considered within the framework of Aalen's multiplicative intensity model. This model includes the filtered data model that, in turn, allows for truncation and/or censoring in addition to accommodating unusual patterns of exposure as well as occurrence. It is shown that the local linear estimators corresponding to all different weightings have the same pointwise asymptotic properties. However, the weighting previously used in the literature in the i.i.d. case is seen to be far from optimal when
it comes to exposure robustness, and a simple alternative weighting is to be preferred. Indeed, this weighting has, effectively, to be well chosen in a ‘pilot' estimator of the survival function as well as in the main estimator itself. We also investigate multiplicative and additive bias correction methods within our framework. The multiplicative bias correction method proves to be best in a simulation study comparing the performance of the considered estimators. An example concerning old age mortality demonstrates the importance of the improvements provided.
Original languageEnglish
Place of publicationAarhus
PublisherCREATES, Institut for Økonomi, Aarhus Universitet
Number of pages39
Publication statusPublished - 2007

    Research areas

  • alen’s multiplicative model; additive bias correction; censoring; counting processes;

See relations at Aarhus University Citationformats

ID: 7141649