Marina Friedrich, Stephan Smeekes, Jean-Pierre Urbain
arXiv 6 Jul 2018 · Statistics — Methodology · publishedJournal of Econometrics (2019) · 35 citations (OpenAlex)
arXiv:1807.02357 · PDF · DOI · OpenAlex · Extracted main text
In this paper we propose an autoregressive wild bootstrap method to construct confidence bands around a smooth deterministic trend. The bootstrap method is easy to implement and does not require any adjustments in the presence of missing data, which makes it particularly suitable for climatological applications. We establish the asymptotic validity of the bootstrap method for both pointwise and simultaneous confidence bands under general conditions, allowing for general patterns of missing data, serial dependence and heteroskedasticity. The finite sample properties of the method are studied in a simulation study. We use the method to study the evolution of trends in daily measurements of atmospheric ethane obtained from a weather station in the Swiss Alps, where the method can easily deal with the many missing observations due to adverse weather conditions.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Smeekes, S. and J.-P. Urbain (2014) A multivariate invariance principle for modified wild bootstrap methods with an application to unit root testing self | 1.000 | 9 | 4 | 100% |
| 2 | Bühlmann, P (1998) Sieve bootstrap for smoothing in nonstationary time series | 0.974 | 13 | 5 | 92% |
| 3 | Franco, B., Bader W., Toon G.C., Bray C., Perrin A., Fischer E.V., S… (2015) Retrieval of ethane from ground-based FTIR solar spectra using improved spectroscopy: Recent burden increase above Jungfraujoch | 0.874 | 9 | 2 | 100% |
| 4 | Shao, X (2010) The dependent wild bootstrap | 0.811 | 4 | 2 | 100% |
| 5 | Chu, C.-K. and J. S. Marron (1991) Comparison of two bandwidths selectors with dependent errors | 0.737 | 3 | 2 | 100% |
| 6 | Hall, P. and J. Horowitz (2013) A simple bootstrap method for constructing nonparametric confidence bands for functions | 0.585 | 3 | 1 | 100% |
| 7 | Neumann, M. H. and J. Polzehl (1998) Simultaneous bootstrap confidence bands in nonparametric regression | 0.585 | 3 | 1 | 100% |
| 8 | Davidson, R. and E. Flachaire (2008) The wild bootstrap, tamed at last | 0.511 | 2 | 1 | 100% |
| 9 | Gregory, K. B., Lahiri, S. N., and D. J. Nordman (2015) A Smooth Block Bootstrap for Statistical Functionals and Time Series | 0.511 | 2 | 1 | 100% |
| 10 | Gregory, K. B., Lahiri, S. N., and D. J. Nordman (2015) A smooth block bootstrap for quantile regression with time series | 0.511 | 2 | 1 | 100% |
Showing the top 10 of 40 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | A statistical analysis of time trends in atmospheric ethane | 0.851 | 13 | 5 |
| 2 | Understanding the explosive trend in EU ETS prices – fundamentals or speculation? | 0.511 | 3 | 2 |
| 3 | Journal of Econometrics | 0.405 | 1 | 1 |
| 4 | High-Dimensional Forecasting in the Presence of Unit Roots and Cointegration | 0.405 | 1 | 1 |