Results 111 to 120 of about 28,224 (283)
Because of the presence of a large amount of noise in high dimensional data due to so many unimportant or less important variables, say nuisance variables, both estimation and inference regarding the variables of interest are difficult in high ...
Drikvandi, Reza
core +1 more source
Private to Public: Deterrent Effects of Bans on Confidential Settlements
Southern Economic Journal, EarlyView.ABSTRACT Nondisclosure agreements are common in the settlement of legal disputes but are controversial as they suppress information that could prevent harm to others. But until the 2017 #MeToo movement, there had been little legislative effort to prohibit the practice in any context, and consequently no evidence on whether public disclosure of harms ...
Blair Druhan Bullock, Joni Hersch
wiley +1 more source
Incidental Versus Random Nuisance Parameters
The Annals of Statistics, 1993 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +3 more sources
Motion Parameter Estimation from Optical Flow without Nuisance Parameters
, 2003 Many kinds of computer vision problems can be formalized as statistical estimation problems with nuisance parameters. In the past, such problems have been solved without making any distinction between the nuisance parameters and structural ones. However,
Naoya Ohta
core
Local Eviction Moratoria and the Spread of COVID‐19
Southern Economic Journal, EarlyView.ABSTRACT At different stages during the initial onset of the COVID‐19 pandemic, various US states and local municipalities enacted eviction moratoria. One of the main aims of these moratoria was to slow the spread of COVID‐19 infections. We deploy a semiparametric difference‐in‐differences approach with an event study specification to examine whether ...
Julia Hatamyar, Christopher F. Parmeter
wiley +1 more source
VIEW, EarlyView.Large‐scale cohorts and multimodal biomedical data have enabled powerful predictive models for clinical risk stratification, but prediction alone cannot guide effective interventions. This review introduces causal artificial intelligence as a design‐first framework that integrates target trial emulation, causal discovery, and robust effect estimation ...
Linlin Cao +5 more
wiley +1 more source
Multiscale scanning with nuisance parameters
We develop a multiscale scanning method to find anomalies in a $d$-dimensional random field in the presence of nuisance parameters. This covers the common situation that either the baseline-level or additional parameters such as the variance are unknown ...
Werner, Frank +2 more
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Bayesian inference: more than Bayes’s theorem
Frontiers in Astronomy and Space SciencesBayesian inference gets its name from Bayes’s theorem, expressing posterior probabilities for hypotheses about a data generating process as the (normalized) product of prior probabilities and a likelihood function.
Thomas J. Loredo, Robert L. Wolpert
doaj +1 more source
Journal of Vinyl and Additive Technology, EarlyView.This study shows that incorporating 5–10 wt.% Posidonia oceanica, with or without micro‐talc, in PBSA preserves thermal stability, modifying crystallization behavior, and maintains good filler dispersion and interfacial adhesion. Mechanical properties are moderately stiffened.
Chiara Pedrotti +8 more
wiley +1 more source
Nuisance parameters, modified profile likelihood and Jacobian prior [PDF]
In a model with nuisance parameters, the maximum likelihood estimators (MLE) of the parameters of interest can be biased. One can reduce the bias due to the presence of the nuisance parameters by removing the O(1) bias of the profile likelihood score. To
Leon-Gonzalez, Roberto, Li, Guangjie
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