Generalised block bootstrap and its use in meteorology
| Autor: | László Zsolt Varga, András Zempléni |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Statistics and Probability
Atmospheric Science 010504 meteorology & atmospheric sciences Computer science Mathematics - Statistics Theory Statistics Theory (math.ST) lcsh:QC851-999 Oceanography 01 natural sciences Vector autoregression 010104 statistics & probability lcsh:Oceanography FOS: Mathematics Test statistic Applied mathematics lcsh:GC1-1581 0101 mathematics 0105 earth and related environmental sciences Block (data storage) Statistical hypothesis testing Applied Mathematics Autocorrelation Data set Sample size determination lcsh:Meteorology. Climatology lcsh:Probabilities. Mathematical statistics lcsh:QA273-280 Block size |
| Zdroj: | Advances in Statistical Climatology, Meteorology and Oceanography, Vol 3, Pp 55-66 (2017) |
| ISSN: | 2364-3587 2364-3579 |
| Popis: | In an earlier paper Rakonczai et al. (2014), we have emphasized the effective sample size for autocorrelated data. The simulations were based on the block bootstrap methodology. However, the discreteness of the usual block size did not allow for exact calculations. In this paper we propose a generalisation of the block bootstrap methodology, relate it to the existing optimisation procedures and apply it to a temperature data set. Our other focus is on statistical tests, where quite often the actual sample size plays an important role, even in case of relatively large samples. This is especially the case for copulas. These are used for investigating the dependencies among data sets. As in quite a few real applications the time dependence cannot be neglected, we investigated the effect of this phenomenon to the used test statistic. The critical values can be computed by the proposed new block bootstrap simulation, where the block sizes are determined e.g. by fitting a VAR model to the observations. The results are illustrated for models of the used temperature data. 18 pages, 5 figures |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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