Similar Search Results

Sequential control of time series by functionals of kernel-weighted empirical processes under local alternatives

Steland, Ansgar - 2003

Motivated in part by applications in model selection in statistical genetics and sequential monitoring of financial data, we study an empirical process framework for a class of stopping rules which rely on kernel-weighted averages of past data. We are interested in the asymptotic distribution...

Persistent link: https://www.econbiz.de/10010306277

Optimal sequential kernel detection for dependent processes

Steland, Ansgar - 2003

In many applications one is interested to detect certain (known) patterns in the mean of a process with smallest delay. Using an asymptotic framework which allows to capture that feature, we study a class of appropriate sequential nonparametric kernel procedures under local nonparametric...

Persistent link: https://www.econbiz.de/10010306289

Data-driven estimation of semiparametric fractional autoregressive models

Beran, Jan; Feng, Yuanhua - 2000

In this paper data-driven algorithms for fitting SEMIFAR models (Beran, 1999) are proposed. The algorithms combine the data-driven estimation of the nonparametric trend and maximum likelihood estimation of the parameters. For selecting the bandwidth, the proposal of Beran and Feng (1999) based...

Persistent link: https://www.econbiz.de/10010324024

Optimal Convergence Rates in Nonparametric Regression with Fractional Time Series Errors

Feng, Yuanhua - 2002

Persistent link: https://www.econbiz.de/10010324049

Simultaneously Modelling Conditional Heteroskedasticity and Scale Change

Feng, Yuanhua - 2002

This paper proposes a semiparametric approach by introducing a smooth scale function into the standard GARCH model so that conditional heteroskedasticity and scale change in a financial time series can be modelled simultaneously. An estimation procedure combining kernel estimation of the scale...

Persistent link: https://www.econbiz.de/10010324081

Modifying the double smoothing bandwidth selector in nonparametric regression

Beran, Jan; Feng, Yuanhua; Heiler, Siegfried - 2000

In this paper a modified double smoothing bandwidth selector, ^h MDS , based on a new criterion, which combines the plug-in and the double smoothing ideas, is proposed. A self-complete iterative double smoothing rule (^h_IDS ) is introduced as a pilot method. The asymptotic properties of both...

Persistent link: https://www.econbiz.de/10010324090

Bahadur Representation for the Nonparametric M-Estimator Under Alpha-mixing Dependence

Cheng, Yebin; de Gooijer, Jan G. - 2005

Under the condition that the observations, which come from a high-dimensional population (X,Y), are strongly stationary and strongly-mixing, through using the local linear method, we investigate, in this paper, the strong Bahadur representation of the nonparametric M-estimator for the unknown...

Persistent link: https://www.econbiz.de/10010325393

New evidence on the finite sample properties of propensity score matching and reweighting estimators

Busso, Matias; DiNardo, John; McCrary, Justin - 2009

Currently available asymptotic results in the literature suggest that matching estimators have higher variance than … reweighting estimators. The extant literature comparing the finite sample properties of matching to specific reweighting … estimators, however, has concluded that reweighting performs far worse than even the simplest matching estimator. We resolve this …

Persistent link: https://www.econbiz.de/10010268994

Generalized single-index models: The EFM approach

Cui, Xia; Härdle, Wolfgang Karl; Zhu, Lixing - 2009

Generalized single-index models are natural extensions of linear models and circumvent the so-called curse of dimensionality. They are becoming increasingly popular in many scientific fields including biostatistics, medicine, economics and financial econometrics. Estimating and testing the model...

Persistent link: https://www.econbiz.de/10010270710

Partial linear quantile regression and bootstrap confidence bands

Härdle, Wolfgang Karl; Ritov, Ya'acov; Song, Song - 2010

In this paper uniform confidence bands are constructed for nonparametric quantile estimates of regression functions. The method is based on the bootstrap, where resampling is done from a suitably estimated empirical density function (edf) for residuals. It is known that the approximation error...

Persistent link: https://www.econbiz.de/10010270724