Problems in scientific time series analysis.

Granville Tunnicliffe Wilson

Qüestiió (1984)

  • Volume: 8, Issue: 1, page 9-19
  • ISSN: 0210-8054

Abstract

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The paper reviews the statistical methods of time series analysis used in a selection of papers from respected scientific journals. In particular, problems are considered in the search for cycles, the use of regression to establish causal links between variables, transfer function modelling and the use of filtering to extract componentes of time series.An attempt is made to assess how useful the ideas of ARMA and Transfer Function modelling might be in improving the efficiency of statistical inference in these contexts.

How to cite

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Tunnicliffe Wilson, Granville. "Problems in scientific time series analysis.." Qüestiió 8.1 (1984): 9-19. <http://eudml.org/doc/40029>.

@article{TunnicliffeWilson1984,
abstract = {The paper reviews the statistical methods of time series analysis used in a selection of papers from respected scientific journals. In particular, problems are considered in the search for cycles, the use of regression to establish causal links between variables, transfer function modelling and the use of filtering to extract componentes of time series.An attempt is made to assess how useful the ideas of ARMA and Transfer Function modelling might be in improving the efficiency of statistical inference in these contexts.},
author = {Tunnicliffe Wilson, Granville},
journal = {Qüestiió},
keywords = {Series temporales; Modelo ARMA; Función de transferencia; Filtros},
language = {eng},
number = {1},
pages = {9-19},
title = {Problems in scientific time series analysis.},
url = {http://eudml.org/doc/40029},
volume = {8},
year = {1984},
}

TY - JOUR
AU - Tunnicliffe Wilson, Granville
TI - Problems in scientific time series analysis.
JO - Qüestiió
PY - 1984
VL - 8
IS - 1
SP - 9
EP - 19
AB - The paper reviews the statistical methods of time series analysis used in a selection of papers from respected scientific journals. In particular, problems are considered in the search for cycles, the use of regression to establish causal links between variables, transfer function modelling and the use of filtering to extract componentes of time series.An attempt is made to assess how useful the ideas of ARMA and Transfer Function modelling might be in improving the efficiency of statistical inference in these contexts.
LA - eng
KW - Series temporales; Modelo ARMA; Función de transferencia; Filtros
UR - http://eudml.org/doc/40029
ER -

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