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
COMPUTING HETEROSCEDASTICITY-ROBUST TESTS OF LINEAR RESTRICTIONS
Date
1987-11-01
Author
Erlat, Haluk
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
37
views
0
downloads
Cite This
Subject Keywords
Statistics, Probability and Uncertainty
,
Economics and Econometrics
,
Statistics and Probability
,
Social Sciences (miscellaneous)
URI
https://hdl.handle.net/11511/63191
Journal
OXFORD BULLETIN OF ECONOMICS AND STATISTICS
DOI
https://doi.org/10.1111/j.1468-0084.1987.mp49004008.x
Collections
Department of Economics, Article
Suggestions
OpenMETU
Core
Analysis of Covariance with Non-normal Errors
ŞENOĞLU, BİRDAL; Avcioglu, Mubeccel Didem (Wiley, 2009-12-01)
P>Analysis of covariance techniques have been developed primarily for normally distributed errors. We give solutions when the errors have non-normal distributions. We show that our solutions are efficient and robust. We provide a real-life example.
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.
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.
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...
Representation of Multiplicative Seasonal Vector Autoregressive Moving Average Models
Yozgatlıgil, Ceylan (Informa UK Limited, 2009-11-01)
Time series often contain observations of several variables and multivariate time series models are used to represent the relationship between these variables. There are many studies on vector autoregressive moving average (VARMA) models, but the representation of multiplicative seasonal VARMA models has not been seriously studied. In a multiplicative vector model, such as a seasonal VARMA model, the representation is not unique because of the noncommutative property of matrix multiplication. In this articl...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
H. Erlat, “COMPUTING HETEROSCEDASTICITY-ROBUST TESTS OF LINEAR RESTRICTIONS,”
OXFORD BULLETIN OF ECONOMICS AND STATISTICS
, pp. 439–445, 1987, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/63191.