Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Robust time series: Some engineering applications
Date
2000-01-01
Author
Tiku, ML
Kestel, Sevtap Ayşe
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
130
views
0
downloads
Cite This
AR(1) models in time series with nonnormal errors represented by two families of distributions: (i) Gamma with support IR:(0,infinity), and (ii) Student's t with support IR:(-infinity,infinity) are considered. Since the maximum likelihood (ML) estimators are intractable, the modified maximum likelihood (MML) estimators of the parameters are derived and it is shown that they are remarkably efficient besides being easy to compute. It is also shown that the least squares (LS) estimators have very low efficiencies and as a consequence, we make a recommendation that their use be limited to normal errors. We give engineering applications. The methodology presented readily extends to AR(q) models.
Subject Keywords
DISTRIBUTIONS
,
ESTIMATORS
,
LOCATION
,
MODELS
URI
https://hdl.handle.net/11511/53329
Conference Name
International Conference on Industrial Technology (IEEE ICIT 2000)
Collections
Graduate School of Applied Mathematics, Conference / Seminar
Suggestions
OpenMETU
Core
Waterfall region analysis for iterative decoding
Yılmaz, Ali Özgür (2004-12-01)
Finite length analysis of iterative decoders can be done by using probabilistic models based on EXIT charts. The validity of these models will be investigated by checking the performance of iterative decoding under various scenarios.
Estimation and hypothesis testing in BIB design and robustness
Tiku, Moti L.; ŞENOĞLU, BİRDAL (Elsevier BV, 2009-07-01)
Modified maximum likelihood estimators of the unknown parameters in a BIB design under non-normality of error distributions are obtained. They are shown to be more efficient and robust than the traditional least squares estimators. A test statistic for testing a linear contrast among treatment effects is developed. A real life example is given.
BenchMetrics: a systematic benchmarking method for binary classification performance metrics
Canbek, Gurol; Taşkaya Temizel, Tuğba; SAĞIROĞLU, ŞEREF (2021-08-01)
This paper proposes a systematic benchmarking method called BenchMetrics to analyze and compare the robustness of binary classification performance metrics based on the confusion matrix for a crisp classifier. BenchMetrics, introducing new concepts such as meta-metrics (metrics about metrics) and metric space, has been tested on fifteen well-known metrics including balanced accuracy, normalized mutual information, Cohen's Kappa, and Matthews correlation coefficient (MCC), along with two recently proposed me...
Similarity matrix framework for data from union of subspaces
Aldroubi, Akram; Sekmen, Ali; Koku, Ahmet Buğra; Cakmak, Ahmet Faruk (2018-09-01)
This paper presents a framework for finding similarity matrices for the segmentation of data W = [w(1)...w(N)] subset of R-D drawn from a union U = boolean OR(M)(i=1) S-i, of independent subspaces {S-i}(i=1)(M), of dimensions {d(i)}(i=1)(M). It is shown that any factorization of W = BP, where columns of B form a basis for data W and they also come from U, can be used to produce a similarity matrix Xi w. In other words, Xi w(i, j) not equal 0, when the columns w(i) and w(j) of W come from the same subspace, ...
Robust Gene Expression Index
Purutçuoğlu Gazi, Vilda (2012-01-01)
The frequentist gene expression index (FGX) was recently developed to measure expression on Affymetrix oligonucleotide DNA arrays. In this study, we extend FGX to cover nonnormal log expressions, specifically long-tailed symmetric densities and call our new index as robust gene expression index (RGX). In estimation, we implement the modified maximum likelihood method to unravel the elusive solutions of likelihood equations and utilize the Fisher information matrix for covariance terms. From the analysis via...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
M. Tiku and S. A. Kestel, “Robust time series: Some engineering applications,” presented at the International Conference on Industrial Technology (IEEE ICIT 2000), GOA, INDIA, 2000, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/53329.