Fitting non-Gaussian persistent data
From MaRDI portal
Publication:2862418
DOI10.1002/ASMB.847zbMath1306.62202OpenAlexW2143087278MaRDI QIDQ2862418
Mauricio Zevallos, Wilfredo Palma
Publication date: 15 November 2013
Published in: Applied Stochastic Models in Business and Industry (Search for Journal in Brave)
Full work available at URL: http://hdl.handle.net/10533/127583
Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Applications of statistics to environmental and related topics (62P12) Economic time series analysis (91B84) Geostatistics (86A32)
Cites Work
- Unnamed Item
- Time series: theory and methods.
- A limit theory for long-range dependence and statistical inference on related models
- Asymptotic theory of statistical inference for time series
- State space modeling of long-memory processes
- An automatic portmanteau test for serial correlation
- Estimation of GARCH Models from the Autocorrelations of the Squares of a Process
- Long‐Memory Time Series
- Fractional differencing
- AN INTRODUCTION TO LONG-MEMORY TIME SERIES MODELS AND FRACTIONAL DIFFERENCING
- On Fractionally Integrated Autoregressive Moving-Average Time Series Models With Conditional Heteroscedasticity
- Theory & Methods: Non‐Gaussian Conditional Linear AR(1) Models
- Likelihood‐based Analysis of a Class of Generalized Long‐Memory Time Series Models
This page was built for publication: Fitting non-Gaussian persistent data
