Similar Search Results

Forecasting daily time series using periodic unobserved components time series models

Koopman, Siem Jan; Ooms, Marius - 2004

We explore a periodic analysis in the context of unobserved components time series models that decompose time series into components of interest such as trend and seasonal. Periodic time series models allow dynamic characteristics to depend on the period of the year, month, week or day. In the...

Persistent link: https://www.econbiz.de/10011342560

Chapter 7 Forecasting with Unobserved Components Time Series Models

Harvey, Andrew - 2006

Structural time series models are formulated in terms of components, such as trends, seasonals and cycles, that have a direct interpretation. As well as providing a framework for time series decomposition by signal extraction, they can be used for forecasting and for ‘nowcasting’. The...

Persistent link: https://www.econbiz.de/10014023699

Chapter 13 Forecasting Seasonal Time Series

Ghysels, Eric; Osborn, Denise R.; Rodrigues, Paulo M.M. - 2006

integrated models and deterministic seasonality models. As well as examining how forecasts are computed in each case, the …. Section 3 discusses less traditional models, specifically nonlinear seasonal models and models for seasonality in variance …. Such nonlinear models primarily concentrate on interactions between seasonality and the business cycle, either using a …

Persistent link: https://www.econbiz.de/10014023693

Persistence and seasonality in the US industrial production index

Caporale, Guglielmo Maria; Gil-Alaña, Luis A.; Poza, Carlos - 2023

values) are taken, evidence of seasonality is obtained; more specifically, deterministic seasonality is rejected in favour of …

Persistent link: https://www.econbiz.de/10014427486

Seasonal adjustment versus seasonality modelling : effect on tourism demand forecasting

Gasmi, Amira - In: Advances in management & applied economics 3 (2013) 4, pp. 119-132

demand for Tunisia, by presenting different techniques of detection of seasonality and the parametric and non …

Persistent link: https://www.econbiz.de/10009762132

Modelling seasonalities in nonlinear inflation rates using SEASETARs

Gooijer, Jan G. de; Vidiella-i-Anguera, Antoni - 2000

) nonlinearityand seasonality simultaneously. The model is termed multiplicativeseasonal SETAR (SEASETAR). It can be viewed as a special … multiplicative constraints in non-multiplicative SETARmodels.These statistics form the basis of a new seasonality-test. We …

Persistent link: https://www.econbiz.de/10011304390

A review of some recent developments in the modelling and seasonal adjustment of infra-monthly time series

Webel, Karsten - 2022

Infra-monthly time series have increasingly appeared on the radar of official statistics in recent years, mostly as a consequence of a general digital transformation process and the outbreak of the COVID-19 pandemic in 2020. Many of those series are seasonal and thus in need for seasonal...

Persistent link: https://www.econbiz.de/10013336397

Seasonal unit root tests under structural breaks

Hassler, Uwe; Rodrigues, Paolo M. M. - 2002

Persistent link: https://www.econbiz.de/10001751667

The Behaviour of Seasonal Unit Root Tests for Quarterly Time Series with Seasonal Mean Shifts

da Silva Lopes, Artur C.B; Montañes, Antonio - 1999

This paper studies the behaviour of the HEGY tests for quarterly data, for seasonal autoregressive unit roots, when the time series being analysed is deterministic seasonal stationary but exhibits a change in the seasonal pattern. As a by-product, we also analyse the HEGY tests for the...

Persistent link: https://www.econbiz.de/10014175046

The Robustness of Tests for Seasonal Differencing to Structural Breaks

da Silva Lopes, Artur C.B - 2000

Resorting to Monte Carlo simulations, the power properties of three simple tests for the seasonal differencing filter are compared when the data contain seasonal mean shifts. Overall, the results favour the HEGY-GLN test as the most robust

Persistent link: https://www.econbiz.de/10014159070