Results 41 to 50 of about 936 (136)
Inference for bounded parameters
The estimation of signal frequency count in the presence of background noise has had much discussion in the recent physics literature, and Mandelkern [1] brings the central issues to the statistical community, leading in turn to extensive discussion by ...
B. P. Roe +21 more
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En muchos problemas de inferencia estadística existe interés en estimar solamente algunos elementos del vector de parámetros que definen el modelo adoptado.
RAFAEL FARIAS +2 more
doaj
This article presents a new dust SED model, named HerBIE, aimed at eliminating the noise-induced correlations and large scatter obtained when performing least-squares fits.
Galliano, F.
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Ignorability for categorical data
We study the problem of ignorability in likelihood-based inference from incomplete categorical data. Two versions of the coarsened at random assumption (car) are distinguished, their compatibility with the parameter distinctness assumption is ...
Jaeger, Manfred
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Panel Data, Local Cuts, and Orthogeodesic Models [PDF]
Orthogeodesic models admit marginal local cuts and therefore separate inference on subparameters is asymptotically justified. Doubly-flat orthogeodesic models admit local cuts marginally and conditionally.
Bent Jesper Christensen, Nicholas Kiefer
core
Implications of macroeconomic volatility in the Euro area [PDF]
In this paper we estimate a Bayesian vector autoregressive model with factor stochastic volatility in the error term to assess the effects of an uncertainty shock in the Euro area.
Böck, Maximilian +4 more
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In recent years, the climate change research community has become highly interested in describing the anthropogenic influence on extreme weather events, commonly termed "event attribution." Limitations in the observational record and in computational ...
Angelil, Oliver +4 more
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Discrete choice non-response [PDF]
Missing values are endemic in the data sets available to econometricians. This paper suggests a unified likelihood-based approach to deal with several nonignorable missing data problems for discrete choice models. Our concern is when either the dependent
Esmerelda A. Ramalho, Richard Smith
core
Nonparametric Conditional Inference for Regression Coefficients with Application to Configural Polysampling [PDF]
We consider inference procedures, conditional on an observed ancillary statistic, for regression coefficients under a linear regression setup where the unknown error distribution is specified nonparametrically.
Ho, Yvonne, Lee, Stephen
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Dual Connections in Nonparametric Classical Information Geometry
We construct an infinite-dimensional information manifold based on exponential Orlicz spaces without using the notion of exponential convergence. We then show that convex mixtures of probability densities lie on the same connected component of this ...
Grasselli, M. R.
core +2 more sources

