Time-Series Models
Time series models of GDP: a reappraisal
... non-linear time series models of real GDP on the basis of the consideration that business-cycle features themselves should motivate a good metric for judging a macroeconomic time-series ...
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Mandelbrot's stochastic time series models
... one-dimensional time series models of the previous sections, to macroscopic fields, for which examples might be a global circulation model or spatial data from a geostation- ary observation ...have ...
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Modeling nonlinearities with mixtures of experts of time series models
... In this paper, we present a survey of the main ideas and results involved in the usage of the ME class of models for time series data. The discussion combines analytical results, simulation ...
22
Poisson qmle of count time series models
... general count time series models. This allows for obtaining optimal predictions without having to specify entirely the conditional distribution. Second, the asymptotic distribution of the estimator ...
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The estimation of parametric change in time-series models
... For model I I , i t may be possible to extend the parameter space s t i l l f u r t h e r , to include i n i t i a l conditions on the model var iable s. Then the in p u t, output and noise terms, with negative indices, ...
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Univariate Time Series Models For Fuel Price
... of Time series more essential in various fields of research, such as business, economics, medicine… ...classical time series ...traditional time series along with fuzzy ...
5
Estimation for vector linear time series models
... Gaussian likelihood (or spectral equivalents to this likelihood) although Gaussianity is not required for any of the results to follow. Chapter 1 gives a brief introduction to the theory of multiple time ...
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Modeling and Forecasting Africa's GDP with Time Series Models
... The main objective of this study is to model and forecast the Gross Domestic Product of Africa using Time Series models. In the study, we present the largest economy of Africa by regions and give a ...
6
Some aspects of estimation for vector time series models
... different models and because of the non-linear nature of the likelihood equa tions this requirement could impose a large computational ...scalar time series models, although it has its origin ...
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A flexible approach to parametric inference in nonlinear and time varying time series models
... regime-switching models have been used with macroeconomic and …nancial ...nonlinear time series models, including those with regime-switching and structural ...from models exhibiting ...
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Analysis of a cross section of time series using structural time series models
... 1 ANALYSIS OF A CROSS SECTION OF TIME SERIES USING STRUCTURAL TIME SERIES MODELS by Pablo Marshall Rivera London School of Economics and Political Science 1990 Submitted to the University of London fo[.] ...
247
Orbital Priors for Time Series Models
... Although we agree that sometimes the Jeffreys’ prior may be useful in that it can penalize the non–identified parameter subspace in the parameter space, see e.g. Kleibergen and van Dijk (1994), Chao and Phillips (1998). ...
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Forecasting wheat production using time series models in Pakistan
... The present study focused on forecasting of wheat production in Pakistan by using various time series models. Keeping in view the close forecast values of production with previous years, ARIMA model ...
6
Long memory and structural breaks in time series models
... of Robinson (1998) to consistently estimate 27r J** f xx (A) f uu (A) dX without having to select a bandwidth. If the condition E (x tutxau3 ) = E {xtx'a) E (utu3) is not valid, the long run variance of x tut has an ...
223
Recursive estimation of non-linear time series models
... A r.ecursive scheme for simultaneous optimal estimation of conditional mean and variance in a nonlinear ARCH (autoregressive con- ditional heteroscedastic) model is also proposed.. Keywo[r] ...
17
A study of estimation procedures for time series models in economics
... found that (i) occurs as well, To some extent multicollinear!ty may be regarded as an identification problem in that it implies an inability to statistically distinguish different estimates and in many cases the only ...
356
Bayesian inference for nonlinear structural time series models
... As expected, the estimated parameter values from all filters are very similar. However, there are notable differences in efficiency and computing time. Table 8 reports the Metropolis- Hastings acceptance rates for ...
30
Inference problems for vector linear time series models
... One reason for considering such models lies in the fact that they are more general than (say) the scalar autoregressive model. Consequently when the number of parameters to be estimated may be restricted by small ...
155
Structural Time Series Models for Business Cycle Analysis
... economic time series has a long tradition, dating back to the 19th century; see the first chapter of Mills (2003) for an historical ...a series, the distinction of what is permanent and what is ...
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Statistical analysis of some financial time series models
... Gram-Charlier series expansions by providing smaller approximation errors in compari- son with the A-type Gram-Charlier expansion and by being less computationally burdensome than the C-type Gram-Charlier ...
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