Author: John L. KnightPublisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 50
Book Description
Empirical Characteristic Function in Time Series Estimation
Author: John L. KnightPublisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 50
Book Description
Empirical Characteristic Function in Time Series Estimation
Author: John KnightPublisher:
ISBN:
Category :
Languages : en
Pages : 41
Book Description
Since the empirical characteristic function (ECF) is the Fourier transform of the empirical distribution function, it retains all the information in the sample but can overcome difficulties arising from the likelihood. This paper discusses an estimation method via the ECF for strictly stationary processes. Under some regularity conditions, the resulting estimators are shown to be consistent and asymptotically normal. The method is applied to estimate the stable ARMA models. For the general stable ARMA model for which the maximum likelihood approach is not feasible, Monte Carlo evidence shows that the ECF method is a viable estimation method for all the parameters of interest. For the Gaussian ARMA model, a particular stable ARMA model, the optimal weight functions and estimating equations are given. Monte Carlo studies highlight the finite sample performances of the ECF method relative to the exact and conditional maximum likelihood methods.
Empirical Characteristics Function in Time Series Estimation and a Test Statistic in Financial Modelling
Author: Time Series Analysis Papers
Author: Emanuel ParzenPublisher:
ISBN:
Category : Time-series analysis
Languages : en
Pages : 588
Book Description
On consistent estimates of the spectral density of a stationary time series; Analysis of a general system for the detection of amplitude-modulated noise; A central limit theorem for multilinear stochastic processes; Conditions that a stochastic process ber egodic; On consistent estimates of the spectrum of a stationary time series; On choosing an estimate of the spectral density function of a stationary time series; On asymptotically efficient consistent estimates of the spectral density function of a stationary time series; General considerations in the analysis of spectra; Mathematical considerations in the estimation of spectra; Spectral analysis of asymptotically stationary time series; On spectral analysis with missing observations and amplitude modulation; Notes on fourier analysis and spectral windows; Statistical inference on time series by Hilbert space methods; An approach to time series analysis; Regression analysis of continuous parameter time series; A new approach to the synthesis of optimal smoothing and prediction systems; Probability density functionals and reproducing kernel hilbert spaces; Extraction and detection problems and reproducing kernel hilbert spaces; On estimation of a probability density function and mode; On models for the probability of fatigue failure of a structure; An approach to empirical time series analysis.
Non-Gaussian Autoregressive-Type Time Series
Author: N. BalakrishnaPublisher: Springer Nature
ISBN: 9811681627
Category : Mathematics
Languages : en
Pages : 238
Book Description
This book brings together a variety of non-Gaussian autoregressive-type models to analyze time-series data. This book collects and collates most of the available models in the field and provide their probabilistic and inferential properties. This book classifies the stationary time-series models into different groups such as linear stationary models with non-Gaussian innovations, linear stationary models with non-Gaussian marginal distributions, product autoregressive models and minification models. Even though several non-Gaussian time-series models are available in the literature, most of them are focusing on the model structure and the probabilistic properties.
Macroeconometrics and Time Series Analysis
Author: Steven DurlaufPublisher: Springer
ISBN: 0230280838
Category : Business & Economics
Languages : en
Pages : 417
Book Description
Specially selected from The New Palgrave Dictionary of Economics 2nd edition, each article within this compendium covers the fundamental themes within the discipline and is written by a leading practitioner in the field. A handy reference tool.
The Analysis of Directional Time Series: Applications to Wind Speed and Direction
Author: Jens BrecklingPublisher: Springer Science & Business Media
ISBN: 1461236886
Category : Mathematics
Languages : en
Pages : 236
Book Description
Given a series of wind speeds and directions from the port of Fremantle the aim of this monograph is to detect general weather patterns and seasonal characteristics. To separate the daily land and sea breeze cycle and other short-term disturbances from the general wind, the series is divided into a daily and a longer term, synoptic component. The latter is related to the atmospheric pressure field, while the former is studied in order i) to isolate particular short-term events such as calms, storms and oscillating winds, and ii) to determine the land and sea breeze cycle which dominates the weather pattern for most of the year. All these patterns are described in detail and are related to the synoptic component of the data. Two time series models for directional data and a new measure of angular association are introduced to provide the basis for certain parts of the analysis.
Continuous Empirical Characteristic Function Estimation of Mixtures of Normal Parameters
Author: Dinghai XuOn Order Statistics in Time Series Analysis
Author: Berlin WuPublisher:
ISBN:
Category : Order statistics
Languages : en
Pages : 186
Book Description
Change Point Analysis for Time Series
Author: Lajos HorváthPublisher: Springer Nature
ISBN: 3031516095
Category :
Languages : en
Pages : 552
Book Description