Time Series Analysis, Forecasting and Control
Time Series Analysis, Forecasting and Control
Forecasting the US unemployment rate
Computational Statistics & Data Analysis - Special issue: Computational econometrics
Bootstrap prediction intervals for autoregressive time series
Computational Statistics & Data Analysis
Forecasting nonlinear time series with neural network sieve bootstrap
Computational Statistics & Data Analysis
Time series clustering based on forecast densities
Computational Statistics & Data Analysis
Forecasting daily time series using periodic unobserved components time series models
Computational Statistics & Data Analysis
Bootstrap prediction for returns and volatilities in GARCH models
Computational Statistics & Data Analysis
Nonparametric variance function estimation with missing data
Journal of Multivariate Analysis
A single-index model procedure for interpolation intervals in time series
Computational Statistics
| Hi-index | 0.03 |
A sieve bootstrap procedure for constructing interpolation intervals for a general class of linear processes is proposed. This sieve bootstrap provides consistent estimators of the conditional distribution of the missing values, given the observed data. A Monte Carlo experiment is used to show the finite sample properties of the sieve bootstrap and finally, the performance of the proposed method is illustrated with a real data example.