Results 41 to 50 of about 13,095 (150)

Optimal Designs’ Robustness to Model Misspecification

, 2021
Simulations considering model misspecification at the design stage (Table 2 in the Manuscript)
Sarah Lotspeich (11426089)
core   +1 more source

Bootstrap confidence sets under model misspecification [PDF]

, 2014
A multiplier bootstrap procedure for construction of likelihood-based confidence sets is considered for finite samples and a possible model misspecification.
Zhilova, Mayya, Spokoiny, Vladimir
core   +1 more source

Newsvendor under Mean-Variance Ambiguity and Misspecification [PDF]

Consider a newsvendor problem with an unknown demand distribution. When addressing the issue of distributional uncertainty, we distinguish ambiguity under which the newsvendor does not differentiate demand distributions of common distributional ...
Chen, Zhi, Wang, Ruodu, Liu, Feng, Wang, Shuming   +3 more
core   +1 more source

A View on Model Misspecification in Uncertainty Quantification

, 2023
An initial version of the current work has been accepted to be presented at BNAIC/BeNeLearn 2022, to which it was submitted on August 27 ...
Yuko Kato, David M. J. Tax, Marco Loog
openaire   +2 more sources

Testing constancy of unconditional variance in volatility models by misspecification and specification tests [PDF]

, 2016
The topic of this paper is testing the hypothesis of constant unconditional variance in GARCH models against the alternative that the unconditional variance changes deterministically over time.
Terasvirta, Timo, Silvennoinen, Annastiina   +1 more
core   +2 more sources

Parameter uncertainties for imperfect surrogate models in the low-noise regime

Machine Learning: Science and Technology
Bayesian regression determines model parameters by minimizing the expected loss, an upper bound to the true generalization error. However, this loss ignores model form error, or misspecification, meaning parameter uncertainties are significantly ...
Thomas D Swinburne, Danny Perez
doaj   +1 more source

Accuracy of attribute estimation in the crossed random effects linear logistic test model: impact of Q-matrix misspecification

Frontiers in Education
A simulation study is designed to explore the accuracy of attribute parameter estimation in the crossed random effects linear logistic test model (CRELLTM) with the impact of Q-matrix misspecification on attribute parameter estimation using the SAS ...
Yi-Hsin Chen, Isaac Y. Li, Chunhua Cao, Yan Wang   +3 more
doaj   +1 more source

Inference in dynamic discrete choice problems under local misspecification

, 2019
Single-agent dynamic discrete choice models are typically estimated using heavily parametrized econometric frameworks, making them susceptible to model misspecification.
Bugni, Federico A., Ura, Takuya
core   +1 more source

Misspecification in dynamic models

, 1990
Within the class of ARMAX models we consider the effects that omitted explanatory processes have on the dynamic shape and the exogeneity properties of economic relations. We show that, under suitable assumptions, a well defined "misspecified" ARMAX model exists and is unique.
openaire   +3 more sources

On misspecifications in regularity and properties of estimators

Electronic Journal of Statistics, 2018
The problem of parameter estimation by the continuous time observations of a deterministic signal in white gaussian noise is considered. The asymptotic properties of the maximul likelihood estimator are described in the asymptotics of small noise (large siglal-to-noise ratio).
Chernoyarov, Oleg V., Kutoyants, Yury A., Trifonov, Andrei P.   +2 more
openaire   +5 more sources