Results 271 to 280 of about 21,776,804 (321)

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
openaire   +2 more sources

Simulation-based Bayesian inference under model misspecification

arXiv.org
Simulation-based Bayesian inference (SBI) methods are widely used for parameter estimation in complex models where evaluating the likelihood is challenging but generating simulations is relatively straightforward.
Ryan P. Kelly, D. Warne, David Frazier, D. Nott, Michael U. Gutmann, Christopher C. Drovandi   +5 more
semanticscholar   +1 more source

Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks: An Extended Investigation

arXiv.org
Recent advances in probabilistic deep learning enable efficient amortized Bayesian inference in settings where the likelihood function is only implicitly defined by a simulation program (simulation-based inference; SBI).
Marvin Schmitt, Paul-Christian Burkner, Ullrich Kothe, Stefan T. Radev   +3 more
semanticscholar   +1 more source

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
openaire   +2 more sources

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.
openaire   +2 more sources

Model misspecification, Bayesian versus credibility estimation, and Gibbs posteriors

Scandinavian Actuarial Journal, 2019
In the context of predicting future claims, a fully Bayesian analysis – one that specifies a statistical model, prior distribution, and updates using Bayes's formula – is often viewed as the gold-standard, while Bühlmann's credibility estimator serves as
Liang Hong, Ryan Martin
semanticscholar   +1 more source

Higher‐order asymptotics under model misspecification

Canadian Journal of Statistics, 1996
AbstractMost of the higher‐order asymptotic results in statistical inference available in the literature assume model correctness. The aim of this paper is to develop higher‐order results under model misspecification. The density functions to O(n−3/2) of the robust score test statistic and the robust Wald test statistic are derived under the null ...
Viraswami, K., Reid, N.
openaire   +2 more sources

Model misspecification in proportional hazards regression

Biometrika, 1995
Summary: The proportional hazards model is frequently used to evaluate the effect of treatment on failure time events in randomised clinical trials. Concomitant variables are usually available and may be considered for use in the primary analyses under the assumption that incorporating them may reduce bias or improve efficiency.
Anderson, Garnet L., Fleming, Thomas R.
openaire   +2 more sources

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
openaire   +1 more source

The Relationship Between the Standardized Root Mean Square Residual and Model Misspecification in Factor Analysis Models

Multivariate Behavioral Research, 2018
We argue that the definition of close fitting models should embody the notion of substantially ignorable misspecifications (SIM). A SIM model is a misspecified model that might be selected, based on parsimony, over the true model should knowledge of the ...
Dexin Shi, Albert Maydeu-Olivares, C. Distefano   +2 more
semanticscholar   +1 more source