Statistical inference based on non-smooth estimating functions

Lihui Tian, John Liu (), Y. Zhao and L. J. Wei

Biometrika, 2004, vol. 91, issue 4, 943-954

Abstract: When the estimating function for a vector of parameters is not smooth, it is often rather difficult, if not impossible, to obtain a consistent estimator by solving the corresponding estimating equation using standard numerical techniques. In this paper, we propose a simple inference procedure via the importance sampling technique, which provides a consistent root of the estimating equation and also an approximation to its distribution without solving any equations or involving nonparametric function estimates. The new proposal is illustrated and evaluated via two extensive examples with real and simulated datasets. Copyright 2004, Oxford University Press.

Date: 2004
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Working Paper: STATISTICAL INFERENCES BASED ON NON-SMOOTH ESTIMATING FUNCTIONS (2004)
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