• No results found

Nonlinear Time series Models

Boosting Techniques for Nonlinear Time Series Models

Boosting Techniques for Nonlinear Time Series Models

... popular nonlinear time series models require a priori the choice of parametric functions which are assumed to be appropriate in specific ...the nonlinear structure between the ...

27

Estimation for nonlinear time series models using estimating equations

Estimation for nonlinear time series models using estimating equations

... In this section we recall Godambe's (1985) theorem on stochastic processes and apply it to obtain optimal estimates for recently proposed nonlinear time series models.. Let {Yt1 td} be a[r] ...

20

Existence of stationary distributions for a class of nonlinear time series models in random environment domain

Existence of stationary distributions for a class of nonlinear time series models in random environment domain

... Existence of stationary distributions for a class of nonlinear time series models in random environment domain Yueheng Wang1, Enwen Zhu1* and Yong Xu2 * Correspondence: engwenzhu@126.com[r] ...

9

A flexible approach to parametric inference in nonlinear time series models

A flexible approach to parametric inference in nonlinear time series models

... Ιν τερmσ οφ Θ τηε ϖαριανχε ιν τηε στατε εθυατιον ιτ ισ χεντερεδ αππροξιmατελψ οϖερ 0:1 ανδ, τηυσ, ωε αρε αλλοωινγ φορ εϖερψτηινγ φροm ϖερψ σmαλλ το mοδερατελψ λαργε σηιφτσ ιν τηε ΑΡ χοε′[r] ...

38

A flexible approach to parametric inference in nonlinear and time varying time series models

A flexible approach to parametric inference in nonlinear and time varying time series models

... of nonlinear time series models, including regime-switching and structural ...change models (e.g. threshold autoregressive models or structural break models such as that ...

38

A new approach to modelling nonlinear time series: introducing the ExpAR ARCH and ExpAR GARCH models and applications

A new approach to modelling nonlinear time series: introducing the ExpAR ARCH and ExpAR GARCH models and applications

... of time series has long been the subject of interest in different ...decades time series were analysed with linear ...other models that can explain and fit real data better than linear ...

19

Nonlinear time series: semiparametric and nonparametric methods

Nonlinear time series: semiparametric and nonparametric methods

... More than thirty years ago, Black and Scholes (1973) assumed a constant volatility to derive their famous option pricing equation. The implied volatility values obtained from this equation show skewness, suggesting that ...

245

Concepts and tools for nonlinear time series modelling

Concepts and tools for nonlinear time series modelling

... performance. Nonlinear forecasting has been ad- dressed, among the others, in Tong [120], Granger and Teräsvirta [69], Franses and van Dijk [62], from a financial prospective, and Fan and Yao [55] which focus on ...

64

Nonlinear exponential autoregressive time series models with conditional heteroskedastic errors with applications to economics and finance

Nonlinear exponential autoregressive time series models with conditional heteroskedastic errors with applications to economics and finance

... of time series has long been the subject of interest in many different fields, but particularly economics and ...decades time series were analysed with linear ...linear models when ...

391

Comparative study of static and dynamic neural network models for nonlinear time series forecasting

Comparative study of static and dynamic neural network models for nonlinear time series forecasting

... these models, which is consistent with Levenberg-Marquardt (LM) Training (Levenberg, 1944 and Marquardt, 1963) and the hyperbolic tangent activation function, is built on Error-Correction Learning Rule and starts ...

18

Nonlinear time series analysis in financial applications

Nonlinear time series analysis in financial applications

... volatility models based on autoregressive conditional heteroskedasticity (ARCH) have been commonly used in capturing some of the stylised facts of financial market ...

307

Noise reduction in nonlinear time series analysis

Noise reduction in nonlinear time series analysis

... linear models since the resultant time series would merely have a number o f discrete spikes in its frequency ...for nonlinear models and possibly one o f the most important lessons to ...

152

Comparing Models for Time Series Analysis

Comparing Models for Time Series Analysis

... solving nonlinear estimation ...from time series data and the researchers apply the technique on a Nikei 225 index and TAIEX index dataset to conclude that their approach produces lower error and ...

28

Essays in high dimensional nonlinear time series analysis

Essays in high dimensional nonlinear time series analysis

... various models, the one that has the minimal forecast error is often deemed opti- ...the time series approach, of which the most commonly used are scale-dependent mea- sures based on the absolute ...

155

Estimation and testing of persistence in nonlinear and cyclical time series

Estimation and testing of persistence in nonlinear and cyclical time series

... these series by performing the Dickey- Fuller test with a linear trend for the null hypothesis of a unit root against the alternative of a stationary ...q) models by means of maximum likelihood techniques, ...

253

Which Methodology is Better for Combining Linear and Nonlinear Models for Time Series Forecasting?

Which Methodology is Better for Combining Linear and Nonlinear Models for Time Series Forecasting?

... linear models and their forecast considerably and consistently more accurately, some other studies have reported inconsistent ...linear models. Taskaya and Casey (2005) compare the performance of linear ...

21

Search for Additive Nonlinear Time Series Causal Models

Search for Additive Nonlinear Time Series Causal Models

... a time series { X } t = { X 1 ,· · · , X t ,· · ·} are generated from a lag T additive non-linear ...non-linear models, for example, X t 2 ,k cannot be a cause of X t 1 , j if t 1 < t 2 , no ...

25

Bayesian inference for nonlinear structural time series models

Bayesian inference for nonlinear structural time series models

... biological models with intractable transition ...rational-expectations models with high signal-to-noise ratios when compared to the standard particle filter and the filter in Murray et ...

30

NONLINEAR TIME SERIES ANALYSIS

NONLINEAR TIME SERIES ANALYSIS

... Nonlinear time series analysis is not as well established and is far less well un- derstood than its linear ...numerical models in the ...popular models we introduce the logistic map ...

18

Information Worth of MinMaxEnt  Models for Time Series

Information Worth of MinMaxEnt Models for Time Series

... through time. In many areas from engineering to economics, patterns of time series are ...of time series. The characteristic property of a time series is that its future ...

8

Show all 10000 documents...

Related subjects