Search Results - subject:"Smoothing parameter"

Let’s fix it: Fixed-b asymptotics versus small-b asymptotics in heteroskedasticity and autocorrelation robust inference

Sun, Yixiao - In: Journal of Econometrics 178 (2014) P3, pp. 659-677

In the presence of heteroscedasticity and autocorrelation of unknown forms, the covariance matrix of the parameter estimator is often estimated using a nonparametric kernel method that involves a lag truncation parameter. Depending on whether this lag truncation parameter is specified to grow at...

Persistent link: https://www.econbiz.de/10010730135

Partially linear modeling of conditional quantiles using penalized splines

Wu, Chaojiang; Yu, Yan - In: Computational Statistics & Data Analysis 77 (2014) C, pp. 170-187

quantiles. Two smoothing parameter selection criteria, Generalized Approximate Cross-validation (GACV) and Schwartz …

Persistent link: https://www.econbiz.de/10011056482

Let’s fix it : fixed- asymptotics versus small- asymptotics in heteroskedasticity and autocorrelation robust inference

Sun, Yixiao - In: Journal of econometrics 178 (2014) 1, pp. 659-677

Persistent link: https://www.econbiz.de/10010257366

On smoothing macroeconomic time series using the modified HP filter

Choudhary, M. Ali; Hanif, M. Nadim; Iqbal, Javed - In: Applied economics 46 (2014) 19/21, pp. 2205-2214

Persistent link: https://www.econbiz.de/10010417302

Topics in Application of Nonparametric Smoothing Splines

Lin, Jiang - 2005

There are two topics in this dissertation. The first topic is 'Smoothing Parameter Selection in Nonparametric … Proportional Hazards Models'.We present a new approach for the automatic selection of the smoothing parameter in nonparametric … covariate. The tests are based on the penalized partial likelihood. By treating the inverse of the smoothing parameter as a …

Persistent link: https://www.econbiz.de/10009431282

Locally Adaptive Function Estimation for Binary Regression Models

Jerak, Alexander; Lang, Stefan - 2003

In this paper we present a nonparametric Bayesian approach for fitting unsmooth or highly oscillating functions in regression models with binary responses. The approach extends previous work by Lang et al. (2002) for Gaussian responses. Nonlinear functions are modelled by first or second order...

Persistent link: https://www.econbiz.de/10010265640

A power comparison between nonparametric regression tests

Zhang, Chunming; Dette, Holger - 2003

In this paper, we consider three major types of nonparametric regression tests that are based on kernel and local polynomial smoothing techniques. Their asymptotic power comparisons are established systematically under the fixed and contiguous alternatives, and are also illustrated through...

Persistent link: https://www.econbiz.de/10010306282

A power comparison between nonparametric regression tests

Zhang, Chunming; Dette, Holger - Institut für Wirtschafts- und Sozialstatistik, … - 2003

Persistent link: https://www.econbiz.de/10009295166

A power comparison between nonparametric regression tests

Zhang, Chunming; Dette, Holger - 2003

Persistent link: https://www.econbiz.de/10010509837

Penalized models to estimate customer survival

Figini, Silvia - In: Statistical Methods and Applications 19 (2010) 1, pp. 141-150

Persistent link: https://www.econbiz.de/10008590996