Semi-Nonparametric Modeling and Estimation∗
نویسنده
چکیده
In this paper it will show how unknown density and distribution functions can be modeled semi-nonparametrically via orthonormal series expansions, and how to estimate semi-nonparametric (SNP) models via a sieve estimation approach. As an application I will focus on the mixed proportional hazard (MPH) model with fixed right censoring and unspecified mixing distribution and baseline hazard. I will show how the MPH model with fixed right censoring can be estimated consistently by an integrated method of moments sieve estimation approach. Another application is the first-price auction model, which will also be discussed, but more briefly than the MPH model.
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تاریخ انتشار 2009