Time series models with asymmetric innovations (vol 30, pg 2227, 2001)

Date

2001-01-01

Author

Akkaya, AD
Tiku, ML

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

118
views

0
downloads

Subject Keywords

Statistics and probability

URI

https://hdl.handle.net/11511/64412

Journal

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS

DOI

https://doi.org/10.1081/sta-100106072

Collections

Department of Chemistry, Article

Suggestions

OpenMETU
Core

Time series AR(1) model for short-tailed distributions Akkaya, AD; Tiku, ML (Informa UK Limited, 2005-04-01) The innovations in AR(1) models in time series have primarily been assumed to have a normal or long-tailed distributions. We consider short-tailed distributions (kurtosis less than 3) and derive modified maximum likelihood (MML) estimators. We show that the MML estimator of 0 is considerably more efficient than the commonly used least squares estimator and is also robust. This paper is essentially the first to achieve robustness to inliers and to various forms of short-tailedness in time series analysis.
Short-tailed distributions and inliers Akkaya, Ayşen (Springer Science and Business Media LLC, 2008-08-01) We consider two families of short-tailed distributions (kurtosis less than 3) and discuss their usefulness in modeling numerous real life data sets. We develop estimation and hypothesis testing procedures which are efficient and robust to short-tailed distributions and inliers.
Estimation and hypothesis testing in multivariate linear regression models under non normality İslam, Muhammed Qamarul (Informa UK Limited, 2017-01-01) This paper discusses the problem of statistical inference in multivariate linear regression models when the errors involved are non normally distributed. We consider multivariate t-distribution, a fat-tailed distribution, for the errors as alternative to normal distribution. Such non normality is commonly observed in working with many data sets, e.g., financial data that are usually having excess kurtosis. This distribution has a number of applications in many other areas of research as well. We use modifie...
Inference for variance components in a mixed model for unbalanced split plot design Guven, B (Informa UK Limited, 2005-01-01) We consider the unbalanced split-plot design with the whole plot and the subplot effect from nonnormal universes. The three estimators for the whole plot effect variance component are obtained. An approximate test for significance of the whole plot effect variance component is presented.
Multiple linear regression model with stochastic design variables İslam, Muhammed Qamarul (Informa UK Limited, 2010-01-01) In a simple multiple linear regression model, the design variables have traditionally been assumed to be non-stochastic. In numerous real-life situations, however, they are stochastic and non-normal. Estimators of parameters applicable to such situations are developed. It is shown that these estimators are efficient and robust. A real-life example is given.

Citation Formats

A. Akkaya and M. Tiku, “Time series models with asymmetric innovations (vol 30, pg 2227, 2001),” COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, pp. 2227–2230, 2001, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/64412.