Results 81 to 90 of about 28,224 (283)

Optimal statistical fault detection with nuisance parameters

, 2003
International audienceFault detection is addressed within a statistical framework. The corresponding inference problem is stated. Particular emphasis is put on dealing with nuisance parameters.
Nikiforov, Igor,, Fouladirad, Mitra
core   +2 more sources

Estimating Functions and Equations: An Essay on Historical Developments with Applications to Econometrics [PDF]

The idea of using estimating functions goes a long way back, at least to Karl Pearson's introduction to the method of moments in 1894. It is now a very active area of research in the statistics literature. One aim of this chapter is to provide an account
Anil K Bera, Yannis Bilias, Pradosh Simlai   +2 more
core  

Asymptotic Efficiency of Estimates for Models with Incidental Nuisance Parameters [PDF]

, 1995
In this paper we show that the well­known asymptotic efficiency bounds for full mixture models remain valid if individual sequences of nuisance parameters are considered.
Strasser, Helmut
core  

Robust Tests of Forecast Accuracy for Factor‐Augmented Regressions With an Application to the Novel EA‐MD‐QD Dataset

Journal of Applied Econometrics, EarlyView.
ABSTRACT We present four novel tests of equal predictive accuracy and encompassing á Pitarakis (2023, 2025) for factor‐augmented regressions. Factors are estimated using cross‐section averages (CAs) of grouped series and our theoretical findings are empirically relevant: asymptotic normality, robustness to an overspecification of the number of factors,
Alessandro Morico, Ovidijus Stauskas
wiley   +1 more source

Doppler stretch and delay Cramer-Rao lower bound for signal with large bandwidth

Известия высших учебных заведений России: Радиоэлектроника, 2016
In this paper Cramer-Rao lower bound of joint Doppler stretch and delay estimation for wideband signal is derived. We use wideband term to denote cases in which narrowband signal model is inappropriate.
I. V. Gogolev
doaj  

Improving the Finite Sample Estimation of Average Treatment Effects Using Double/Debiased Machine Learning With Propensity Score Calibration

Journal of Applied Econometrics, EarlyView.
ABSTRACT Double/debiased machine learning (DML) uses for estimating an average treatment effect (ATE) a double‐robust score function that relies on the prediction of nuisance functions, such as the propensity score, which is the probability of treatment assignment given covariates.
Daniele Ballinari, Nora Bearth
wiley   +1 more source

Constructing Optimal Tests on a Lagged Dependent Variable [PDF]

Via the leading unit root case, the problem of testing on a lagged dependent variable is characterized by a nuisance parameter which is present only under the alternative (see Andrews and Ploberger (1994)).
Patrick Marsh
core  

A Joint Test of Unconfoundedness and Common Trends

Journal of Applied Econometrics, EarlyView.
ABSTRACT We introduce an overidentification test of two alternative assumptions to identify the average treatment effect on the treated in a two‐period panel data setting: unconfoundedness and common trends. Under unconfoundedness, treatment assignment and post‐treatment outcomes are independent, conditional on control variables and pre‐treatment ...
Martin Huber, Eva‐Maria Oeß
wiley   +1 more source

Approximating posteriors with high-dimensional nuisance parameters via integrated rotated Gaussian approximation. [PDF]

Biometrika, 2021
VAN DEN Boom W, Reeves G, Dunson DB.
europepmc   +1 more source

Note on randomized filtered experiments in presence of nuisance parameters [PDF]

, 2001
In this report we define randomized filtered experiments with an abstract parameter space consisting not only parameters of interest but also nuisance parameters.
Dzhaparidze, Kacha, Dzhaparidze, K.O. (Kacha)   +1 more
core