Results 31 to 40 of about 23,103 (324)
Statistical Modelling, 2008 A common problem in statistical modelling is to distinguish between finite mixture distribution and a homogeneous non-mixture distribution. Finite mixture models are widely used in practice and often mixtures of normal densities are indistinguishable from homogenous non-normal densities.
Tarpey, Thaddeus +2 more
openaire +4 more sources
Stable Prediction with Model Misspecification and Agnostic Distribution Shift [PDF]
AAAI Conference on Artificial Intelligence, 2020 For many machine learning algorithms, two main assumptions are required to guarantee performance. One is that the test data are drawn from the same distribution as the training data, and the other is that the model is correctly specified.
K. Kuang +4 more
semanticscholar +1 more source
Model Misspecification as the Causes of Flypaper Effect
Proceedings, 2023 The aim of this paper is to investigate the relationship between the Fly-paper effect (FPE) and possible errors in the specification of econometric models used in the empirical analysis of FPE.
Siniša Mali
doaj +1 more source
Robust control and model misspecification [PDF]
Journal of Economic Theory, 2006 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lars Peter Hansen +3 more
openaire +1 more source
Mathematics, 2021 In optimal experimental design theory it is usually assumed that the response variable follows a normal distribution with constant variance. However, some works assume other probability distributions based on additional information or practitioner’s ...
Sergio Pozuelo-Campos +2 more
doaj +1 more source
Optimal Designs’ Robustness to Model Misspecification [PDF]
, 2021 Simulations considering model misspecification at the design stage (Table 2 in the Manuscript)
Sarah Lotspeich (11426089)
core +1 more source
Comparing performance between log-binomial and robust Poisson regression models for estimating risk ratios under model misspecification. [PDF]
BMC Med Res Methodol, 2018 BackgroundLog-binomial and robust (modified) Poisson regression models are popular approaches to estimate risk ratios for binary response variables. Previous studies have shown that comparatively they produce similar point estimates and standard errors ...
Chen W, Qian L, Shi J, Franklin M.
europepmc +2 more sources
Likelihood-based estimation and prediction for a measles outbreak in Samoa
Infectious Disease Modelling, 2023 Prediction of the progression of an infectious disease outbreak is important for planning and coordinating a response. Differential equations are often used to model an epidemic outbreak's behaviour but are challenging to parameterise. Furthermore, these
David Wu +4 more
doaj +1 more source
Quality and Reliability Engineering International, 2021 The design of constant‐stress accelerated life‐test (CSALT) is important in reliability estimation. In reliability studies, practitioners usually rely on underlying distribution to design CSALTs.
N. Balakrishnan, E. Castilla, M. Ling
semanticscholar +1 more source
Propensity score weighting under limited overlap and model misspecification [PDF]
Statistical Methods in Medical Research, 2020 Propensity score weighting methods are often used in non-randomized studies to adjust for confounding and assess treatment effects. The most popular among them, the inverse probability weighting, assigns weights that are proportional to the inverse of ...
Yunji Zhou +2 more
semanticscholar +1 more source