Home  About us  Contact
 

Semiparametric Estimator (semiparametric + estimator)

Distribution by Scientific Domains
Mathematics and Statistics50%

Selected Abstracts

A Semiparametric Estimator of the Crossing Point in the Two-Sample Linear Shift Function: Application to Crossing Lifetime Distributions

BIOMETRICAL JOURNAL, Issue 2 2004
Chi-tsung Wu
Abstract Let X and Y be two random variables with continuous distribution functions F and G. Consider two independent observations X1, , , Xm from F and Y1, , , Yn from G. Moreover, suppose there exists a unique x* such that F(x) > G(x) for x < x* and F(x) < G(x) for x > x* or vice versa. A semiparametric model with a linear shift function (Doksum, 1974) that is equivalent to a location-scale model (Hsieh, 1995) will be assumed and an empirical process approach (Hsieh, 1995) is used to estimate the parameters of the shift function. Then, the estimated shift function is set to zero, and the solution is defined to be an estimate of the crossing-point x*. An approximate confidence band of the linear shift function at the crossing-point x* is also presented, which is inverted to yield an approximate confidence interval for the crossing-point. Finally, the lifetime of guinea pigs in days observed in a treatment-control experiment in Bjerkedal (1960) is used to demonstrate our procedure for estimating the crossing-point. (© 2004 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source]

An Efficient Taper for Potentially Overdifferenced Long-memory Time Series

JOURNAL OF TIME SERIES ANALYSIS, Issue 2 2000
Clifford M. Hurvich
We propose a new complex-valued taper and derive the properties of a tapered Gaussian semiparametric estimator of the long-memory parameter d, (,0.5, 1.5). The estimator and its accompanying theory can be applied to generalized unit root testing. In the proposed method, the data are differenced once before the taper is applied. This guarantees that the tapered estimator is invariant with respect to deterministic linear trends in the original series. Any detrimental leakage effects due to the potential noninvertibility of the differenced series are strongly mitigated by the taper. The proposed estimator is shown to be more efficient than existing invariant tapered estimators. Invariance to kth order polynomial trends can be attained by differencing the data k times and then applying a stronger taper, which is given by the kth power of the proposed taper. We show that this new family of tapers enjoys strong efficiency gains over comparable existing tapers. Analysis of both simulated and actual data highlights potential advantages of the tapered estimator of d compared with the nontapered estimator. [source]

Semiparametric Estimation of a Duration Model

OXFORD BULLETIN OF ECONOMICS & STATISTICS, Issue 5 2001
A. Alonso Anton
Within the framework of the proportional hazard model proposed in Cox (1972), Han and Hausman (1990) consider the logarithm of the integrated baseline hazard function as constant in each time period. We, however, proposed an alternative semiparametric estimator of the parameters of the covariate part. The estimator is considered as semiparametric since no prespecified functional form for the error terms (or certain convolution) is needed. This estimator, proposed in Lewbel (2000) in another context, shows at least four advantages. The distribution of the latent variable error is unknown and may be related to the regressors. It takes into account censored observations, it allows for heterogeneity of unknown form and it is quite easy to implement since the estimator does not require numerical searches. Using the Spanish Labour Force Survey, we compare empirically the results of estimating several alternative models, basically on the estimator proposed in Han and Hausman (1990) and our semiparametric estimator. [source]