Testing for multivariate heteroscedasticity

@article{Holgersson2004TestingFM,
  title={Testing for multivariate heteroscedasticity},
  author={H. E. T. Holgersson and Ghazi Shukur},
  journal={Journal of Statistical Computation and Simulation},
  year={2004},
  volume={74},
  pages={879 - 896}
}
In this article, we propose a testing technique for multivariate heteroscedasticity, which is expressed as a test of linear restrictions in a multivariate regression model. Four test statistics with known asymptotical null distributions are suggested, namely the Wald, Lagrange multiplier (LM), likelihood ratio (LR) and the multivariate Rao F-test. The critical values for the statistics are determined by their asymptotic null distributions, but bootstrapped critical values are also used. The… 

Testing for Panel Unit Roots under General Cross-sectional Dependence

TLDR
This article generalizes four tests of multivariate linear hypothesis to panel data unit root testing and demonstrates that all four tests remains well behaved in cases of where there are heterogeneous alternatives and cross-correlations between marginal variables.

Depth based inference on conditional distribution with infinite dimensional data.

We develop inference and testing procedures for conditional dispersion and skewness in a nonparametric regression setup based on statistical depth functions. The methods developed can be applied in

On Nonparametric Regression using Data Depth

We investigate nonparametric regression methods based on statistical depth functions. These nonparametric regression procedures can be used in situations, where the response is multivariate and the

Understanding Uncertainty Maps in Vision with Statistical Testing

TLDR
This paper shows how revisiting results from Random Field theory (RFT) when paired with DNN tools (to get around computational hur-dles) leads to efficient frameworks that can provide a hypothesis test capabilities, not otherwise available, for uncertainty maps from models used in many vision tasks.

Multivariate statistical techniques and water quality assessment: Discourse and review on some analytical models

Regular monitoring and comprehensive assessment of water quality and its associated processes require sophisticated analytical models to reveal concealed instruments controlling their properties.

Assessing Distributional Properties of High-Dimensional Data

TLDR
This doctoral thesis consists of five papers in the field of multivariate statistical analysis of high-dimensional data that have wide application and methodological scope and the individual papers are representative of their respective fields.

Analysis of Import Demand for Wooden Beds in the U.S.

The market of wooden beds in the U.S. has been flooded with imports from China and Vietnam in recent years. Static and dynamic Almost Ideal Demand System models are used to assess the import demand

The Correlation of Urban Cluster and Cultural Industry Cluster

The development of urban cluster and cultural industry cluster complement each other. Exploring the inner correlation between the development of the urban cluster and cultural industry cluster from

References

SHOWING 1-10 OF 33 REFERENCES

Size and Power of the Error Correction Model Cointegration Test. A Bootstrap Approach

The size and power of the ECM cointegration test are investigated by using the 'bootstrap critical values.' The purpose of this paper is to show the ability of the bootstrap technique to produce

Some Tests for Homoscedasticity

Abstract Two exact tests are presented for testing the hypothesis that the residuals from a least squares regression are homoscedastic. The results can be used to test the hypothesis that a linear

A simple test for heteroscedasticity and random coefficient variation (econometrica vol 47

A simple test for heteroscedastic disturbances in a linear regression model is developed using the framework of the Lagrangian multiplier test. For a wide range of heteroscedastic and random

Using Residuals Robustly I: Tests for Heteroscedasticity, Nonlinearity

Introduction. In the past few years a variety of methods has been proposed for estimating the parameters of a linear model which are less sensitive to departures from normality of the error

Testing autocorrelation in a system perspective testing autocorrelation

The Breusch-Godfrey test for autocorrelated errors is generalised to cover systems of equations, and the properties of 18 versions of the test are studied using Monte Carlo methods. We show that only

The small sample properties of the reset test as applied to systems of equations

The RESET test for functional misspecification is generalised to cover systems of equations, and the properties of 7 versions are studied using Monte Carlo methods. The Rao F -test clearly exhibits

An extension of a standard test for heteroskedasticity to a systems framework

Estimation and inference in econometrics

TLDR
A theme of the text is the use of artificial regressions for estimation, reference, and specification testing of nonlinear models, including diagnostic tests for parameter constancy, serial correlation, heteroscedasticity, and other types of mis-specification.

Tests for Specification Errors in Classical Linear Least‐Squares Regression Analysis

SUMMARY The effects on the distribution of least-squares residuals of a series of model mis-specifications are considered. It is shown that for a variety of specification errors the distributions of

The Theory and Practice of Econometrics

TLDR
The Classical Inference Approach for the General Linear Model, Statistical Decision Theory and Biased Estimation, and the Bayesian Approach to Inference are reviewed.