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Bayesian Asymptotics Under Misspecification

, 2004
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Quantile Regression under Local Misspecification

Acta Mathematicae Applicatae Sinica, English Series, 2020
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Duan, Xiao-gang, Wang, Qi-hua
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Model Misspecification and Underdiversification

The Journal of Finance, 2001
AbstractIn this paper, we study intertemporal portfolio choice when an investor accounts explicitly for model misspecification. We develop a framework that allows for ambiguity about not just the joint distribution of returns for all stocks in the portfolio, but also for different levels of ambiguity for the marginal distribution of returns for any ...
Uppal, Raman, Wang, Tan
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Position Estimation under Model Misspecification

2017 IEEE 86th Vehicular Technology Conference (VTC-Fall), 2017
When time-based radio range measurements between network nodes are perturbed by a line-of-sight blocking obstacle, position estimation accuracy degrades significantly. The perturbation is caused by multipath propagation or excess delays since waves travel at slower speed while piercing the obstacles.
Mendrzik, Rico, Bauch, Gerhard
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Regression Diagnostic under Model Misspecification

Journal of Applied Statistics, 2007
We propose two novel diagnostic measures for the detection of influential observations for regression parameters in linear regression. Traditional diagnostic statistics focus on the effect of deletion of data points either on parameter estimates, or on predicted values.
Li-Chu, Chien, Tsung-Shan, Tsou
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Model Misspecification and Multipoint Linkage Analysis

Human Heredity, 1992
Pairwise linkage analysis is robust to genetic model misspecification provided dominance is correctly specified, the primary effect being inflation of the recombination fraction. By contrast, we show that multipoint analysis under misspecified models is not robust when a putative disease locus is placed between close flanking markers, with potentially ...
N, Risch, L, Giuffra
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The Misspecification of Arma Models

Statistica Neerlandica, 1989
The object of this paper is to assess the effects of fitting a model of the wrong order to a time series which is generated by an autoregressive moving–average process. The method is to examine the spectral density functions which are indicated by the probability limits of the least–squares estimators of the misspecified models.
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Misspecification in event studies

Journal of Corporate Finance, 2017
Abstract We examine the statistical error and efficiency associated with two commonly used event-study techniques when applied to samples of various sizes. Previous research has established that the frequently used Patell (1976) test is not well specified when the event itself creates additional return variance.
Joseph M. Marks, Jim Musumeci
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Bootstrapping fMRI Data: Dealing with Misspecification

Neuroinformatics, 2015
The validity of inference based on the General Linear Model (GLM) for the analysis of functional magnetic resonance imaging (fMRI) time series has recently been questioned. Bootstrap procedures that partially avoid modeling assumptions may offer a welcome solution.
Sanne P, Roels, Beatrijs, Moerkerke, Tom, Loeys   +2 more
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Diagnostics of model misspecification

1996
In section 1.2, we denoted the true regression relationship between Y and x by µ(x), and we noted that µ(x) is generally unknown, although in practice it is approximated by a parametric function f (x, θ). Because we use this f to make some statistical inferences, however, we must be able to determine whether or not our choice of f is accurate.
Sylvie Huet, Annie Bouvier, Marie-Anne Gruet, Emmanuel Jolivet   +3 more
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