Results 21 to 30 of about 246,485 (302)

Applying Wald's Variance Component Test

open access: yesThe Annals of Statistics, 1983
In this note a generalization of a variance component test that was first suggested by Wald is examined. Necessary and sufficient conditions are given for the test to be applicable in a mixed linear model. A uniqueness property of the test in terms of degrees of freedom is also obtained.
Seely, Justus F., El-Bassiouni, Yahia
openaire   +2 more sources

Testing for zero-modification in count regression models [PDF]

open access: yes, 2006
Count data often exhibit overdispersion and/or require an adjustment for zero outcomes with respect to a Poisson model. Zero-modified Poisson (ZMP) and zero-modified generalized Poisson (ZMGP) regression models are useful classes of models for such ...
Czado, Claudia, Min, Aleksey
core   +2 more sources

A Tutorial on Testing the Equality of Standardized Regression Coefficients in Structural Equation Models using Wald Tests with lavaan [PDF]

open access: yesTutorials in Quantitative Methods for Psychology, 2020
Comparing the effects of two or more explanatory variables on a dependent variable in structural equation models, with either manifest or latent variables, may be hampered by the arbitrary metrics which are common in social sciences and psychology.
Klopp, Eric
doaj   +1 more source

Formulating Wald Tests of Nonlinear Restrictions

open access: yesEconometrica, 1985
On montre a partir de l'evidence de Monte Carlo que les differences dans la forme fonctionnelle des restrictions non lineaires sont importantes dans les petites tailles d ...
Gregory, Allan W, Veall, Michael R
openaire   +2 more sources

Power comparison among tests for fractional unit roots [PDF]

open access: yes, 2008
This article compares the asymptotic power properties of the Wald, the Lagrange Multiplier and the Likelihood Ratio test for fractional unit roots. The paper shows that there is an asymptotic inequality between the three tests that holds under fixed ...
Lobato, Ignacio N., Velasco, Carlos
core   +3 more sources

Fixed-b Inference for Testing Structural Change in a Time Series Regression

open access: yesEconometrics, 2016
This paper addresses tests for structural change in a weakly dependent time series regression. The cases of full structural change and partial structural change are considered.
Cheol-Keun Cho, Timothy J. Vogelsang
doaj   +1 more source

Rao and Wald Tests in Nonzero-Mean Non–Gaussian Sea Clutter

open access: yesRemote Sensing
The non-Gaussian nature of radar-observed clutter echoes induces performance degradation in the context of remote sensing target detection when using conventional Gaussian detectors. To enhance target detection performance, this study addresses the issue
Haoqi Wu   +3 more
doaj   +1 more source

Un approccio robusto alla verifica d'ipotesi basato sulla funzione di verosomiglianza pesata

open access: yesStatistica, 2007
Weighted version of the Likelihood Ratio, Wald and score tests are proposed for parametric inference. If the parametric model is correct, the Weighted Likelihood tests are asymptotically equivalent to the corresponding Likelihood tests.
Claudio Agostinelli
doaj   +1 more source

Wald tests of singular hypotheses

open access: yesBernoulli, 2016
Motivated by the problem of testing tetrad constraints in factor analysis, we study the large-sample distribution of Wald statistics at parameter points at which the gradient of the tested constraint vanishes. When based on an asymptotically normal estimator, the Wald statistic converges to a rational function of a normal random vector.
Drton, Mathias, Xiao, Han
openaire   +4 more sources

Validating attribute hierarchies in cognitive diagnosis models

open access: yesFrontiers in Psychology
Cognitive diagnosis models (CDMs) are restricted latent class models that are widely used in educational and psychological fields. Attribute hierarchy, as an important structural feature of the CDM, can provide critical information for inferring ...
Xueqin Zhang   +3 more
doaj   +1 more source

Home - About - Disclaimer - Privacy