The bad small sample performance of unit root tests is well known and depends partly on the existence of nuisance parameters. To deal with this Johansen (2004) presents a small sample correction of the Dickey-Fuller test. The correction factor depends on biased parameter estimates. The purpose of this study is to, through simulation, compare the small sample correction with a bootstrap approach...

Background: Accurate brain tissue segmentation from magnetic resonance (MR) images is an important step in analysis of cerebral images. There are software packages which are used for brain segmentation. These packages usually contain a set of skull stripping, intensity non-uniformity (bias) correction and segmentation routines. Thus, assessment of the quality of the segmented gray matter (GM), ...

We propose an analytical bias correction for the maximum likelihood estimators of the G0 I distribution. This distribution is a very powerful tool for speckled imagery analysis, since it is capable of describing a wide range of target roughness. We compare the performance of the corrected estimators with the corresponding original version using Monte Carlo simulation. This second-order bias cor...

Grasse DW, Moxon KA. Correcting the bias of spike field coherence estimators due to a finite number of spikes. J Neurophysiol 104: 548–558, 2010. First published May 19, 2010; doi:10.1152/jn.00610.2009. The coherence between oscillatory activity in local field potentials (LFPs) and single neuron action potentials, or spikes, has been suggested as a neural substrate for the representation of inf...

Nonparametric methods play a central role in modern empirical work. While they provide inference procedures that are more robust to parametric misspecification bias, they may be quite sensitive to tuning parameter choices. We study the effects of bias correction on confidence interval coverage in the context of kernel density and local polynomial regression estimation, and prove that bias corre...

The transition to renewables requires storage to help smooth short-term variations in energy from wind and solar sources, as well as to respond to spikes in electricity spot prices, which can easily exceed 20 times their average. Efficient operation of an energy storage device is a fundamental problem, yet classical algorithms such asQ-learning can diverge for millions of iterations, limiting p...

Longitudinal MR imaging is increasingly being used to measure cerebral atrophy progression in dementia and other neurological disorders. Differences in intensity inhomogeneity between serial scans can confound these measurements. This differential bias also distorts nonlinear registration and makes both manual and automated segmentation of tissue type less reliable. A technique is described for...

Data quality from poor and socially deprived regions have given rise to many statistical challenges. One of them is the underreporting vital events leading biased estimates for associated risks. To deal with underreported count data, models based on compound Poisson distributions been commonly assumed. be identifiable, such usually require extra strong information about probability reporting ev...