We propose jackknife empirical likelihood (EL) methods for constructing confidence intervals of mean with regression imputation that allows ignorable or nonignorable missingness. The confidence interval is constructed based on the adjusted jackknife pseudo-values (Rao and Shao, 1992). The...

Lending is associated with credit risk. Modelling the loss stochastically, the cost of credit risk is the expected loss. In credit business the probability that the debtor will default in payments within one year, often is the only reliable quantitative parameter. Modelling the time to default...

Lending is associated with credit risk. Modelling the loss stochastically, the cost of credit risk is the expected loss. In credit business the probability that the debtor will default in payments within one year, often is the only reliable quantitative parameter. Modelling the time to default...

This paper challenges the assumption that the inflation process within the euro area is well-described by a linear Phillips curve and investigates in a nonparametric framework how inflation is sensitive to output growth. An asymmetric output-inflation trade-off is pointed out in the euro area at...

We present a local linear estimator with variable bandwidth for multivariate nonparametric regression. We prove its consistency and asymptotic normality in the interior of the observed data and obtain its rates of convergence. This result is used to obtain practical direct plug-in bandwidth...

Abstract The bivariate kernel density-ratio estimator has developed popularity among epidemiologists as a flexible exploratory tool for examining the spatial variation in the risk of disease. This estimator is simply given as the quotient of a “case” density estimate describing the observed...

This paper gives a selective review on some recent developments of nonparametric methods in both continuous and discrete time finance, particularly in the areas of nonparametric estimation and testing of diffusion processes, nonparametric testing of parametric diffusion models, nonparametric...

We study nonparametric estimation of regression function with nonstationary (integrated or nearly integrated) covariates and the error series of the regressor process following a fractional ARIMA model. A local linear estimation method is developed to estimate the unknown regression function....