SYMARMA: a new dynamic model for temporal data on conditional symmetric distribution
type: Item
instance of: scholarly article
published in: Statistical Papers
volume: 59
issue: 1
page(s): 75-97
publication date: 2016-02-20T00:00:00Z
publication date: 2018-03-22T00:00:00Z
author: Vinicius Q. S. Maior
author: Francisco José A. Cysneiros
title: SYMARMA: a new dynamic model for temporal data on conditional symmetric distribution
zbMATH Open document ID: 1416.62509
review text: The authors propose a new class of models under the assumption that the random component has conditionally a continuous symmetric distribution, while the dynamic component has the form of ARMA structure. A conditional maximum likelihood estimator of the unknown parameter is derived and an iterative procedure for the estimation is presented. Some simulation studies are given to present the performances of the obtained estimator. The application on the time series of excess return in the daily closing prices in some indexes is discussed.
reviewed by: Miroslav M. Ristić
Mathematics Subject Classification ID: 62M10
Mathematics Subject Classification ID: 62P05
zbMATH DE Number: 6852091
zbMATH Keywords: conditional maximum likelihood
zbMATH Keywords: outlier
zbMATH Keywords: symmetric distributions
zbMATH Keywords: time series
describes a project that uses: R
describes a project that uses: bootstrap
MaRDI profile type: Publication
full work available at URL: s00362-016-0753-z
OpenAlex ID: W2275139945
cites work: Generalized Autoregressive Moving Average Models
cites work: Heteroscedasticity and/or autocorrelation diagnostics in nonlinear models with AR(1) and symmetrical errors
cites work: Joint Estimation of Model Parameters and Outlier Effects in Time Series
cites work: Q3922034
cites work: Q4101268
cites work: Restricted methods in symmetrical linear regression models
cites work: Q4318617
cites work: Q3996150
cites work: On influence diagnostic in univariate elliptical linear regression models
cites work: Time Series Models Based on Generalized Linear Models: Some Further Results
cites work: On a measure of lack of fit in time series models
cites work: Robustness of the student t based M-estimator
cites work: Robust statistical modeling using the Birnbaum‐Saunders‐t distribution applied to insurance
cites work: Q3991247
cites work: Q4820980
cites work: Beta autoregressive moving average models
cites work: A regression model for time series of counts
cites work: Markov Regression Models for Time Series: A Quasi-Likelihood Approach
DOI: 10.1007/S00362-016-0753-Z
description: scientific article; zbMATH DE number 6852091