Results 21 to 30 of about 25,591 (263)
Seasonality with Trend and Cycle Interactions in Unobserved Components Models [PDF]
SummaryUnobserved components time series models decompose a time series into a trend, a season, a cycle, an irregular disturbance and possibly other components. These models have been successfully applied to many economic time series. The standard assumption of a linear model, which is often appropriate after a logarithmic transformation of the data ...
Siem Jan Koopman, Kai Ming Lee
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COVID-19 Data Imputation by Multiple Function-on-Function Principal Component Regression
The aim of this paper is the imputation of missing data of COVID-19 hospitalized and intensive care curves in several Spanish regions. Taking into account that the curves of cases, deceases and recovered people are completely observed, a function-on ...
Christian Acal +3 more
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Fad Models with Markov Switching Hetroskedasticity: Decomposing Tehran Stock Exchange Return into Permanent and Transitory Components [PDF]
In this paper, the stochastic behavior of Tehran stock exchange return index (TEDPIX) is examined by using unobserved component Markov switching model (UC-MS) during the period 3/27/2010 - 8/3/2015.
Teimour Mohammadi +3 more
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Macro-Prudential Policies and Financial Cycle in Iran [PDF]
Financial markets are channels for attracting surplus financial resources and allocating them to investment. Macro-prudential policy needs to consider financial cycle in order to assess the state of the financial sector, predict its developments and ...
Nafiseh Keshtgar +2 more
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Bayesian analysis of output gap in Barbados
This article contributes to understanding the performance of various unobserved components (UC) models in fitting Barbados’ real GDP. Relying on recent UC models techniques, it finds support for the UC model that captures correlated disturbances, but not
Terence D. Agbeyegbe
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Approximate state space modelling of unobserved fractional components [PDF]
We propose convenient inferential methods for potentially nonstationary multivariate unobserved components models with fractional integration and cointegration. Based on finite-order ARMA approximations in the state space representation, maximum likelihood estimation can make use of the EM algorithm and related techniques. The approximation outperforms
Hartl, Tobias, Weigand, Roland
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ObjectiveTo quantify the increase in pediatric patients presenting to the emergency department with suicidality before and during the COVID-19 pandemic, and the subsequent impact on emergency department length of stay and boarding.MethodsThis ...
Amy R Zipursky +6 more
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Measuring business cycles: Empirical evidence based on an unobserved component approach
We adopt an unobserved components time series model to track the business cycles in the G7 countries using the Industrial production index over the period from 1:1961 to 8:2017. The advantage of adopting the industrial production series frequency is that
Huthaifa Alqaralleh
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Time Series Forecasting with UCM Model ; A Comparative Study using the Tigris River Data [PDF]
In this paper,we build two basic models to forecast a flow water of the Tigris river which enters to mosul city . The first model is Unobserved Components Model which is writing braivly by UCM,the second is Autoregressive and Moving Average model which
Thafer Ramathan Muttar +1 more
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Martingale unobserved component models [PDF]
AbstractThis chapter generalizes the familiar linear Gaussian unobserved component models or structural time series models to martingale unobserved component models. This generates forecasts whose rate of discounting of data is time-varying or local.
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