We develop nearly unbiased estimators for the two-parameter Birnbaum–Saunders distribution [Birnbaum, Z.W., Saunders, S.C., 1969a. A new family of life distributions. J. Appl. Probab. 6, 319–327], which is commonly used in reliability studies. We derive modified maximum likelihood estimators that are bias-free to second order. We also consider bootstrap-based bias correction. The numerical evid...

This paper develops a bias correction scheme for a multivariate heteroskedastic errors-in-variables model. The applicability of this model is justified in areas such as astrophysics, epidemiology and analytical chemistry, where the variables are subject to measurement errors and the variances vary with the observations. We conduct Monte Carlo simulations to investigate the performance of the co...

In applications of (nonlinear) model predictive control a more and more common approach for the state estimation is to use moving horizon estimation, which employs (nonlinear) optimization directly on a model for a whole batch of data. This paper shows that horizon estimation may also be used for joint parameter estimation and state estimation, as long as a bias correction based on the Kalman f...

The paper evaluates two different bias correction schemes for Vaisala RS92 measurements. Given that RS92 sensors are used globally to measure tropospheric humidity, the comparison is valuable. Because of my interest in the topic, I am providing a few comments that may help to improve the paper. However, please note that the comments here should not be considered as editor’s decision but solely ...

introduction evaluation of the delivered dose of externally wedged photon beams by external diode dosimeters during the treatment process requires the estimation of exit surface dose correction factors in various wedge angles and field sizes. materials and methods a system of absorbed dose evaluation, using p-type diode dosimeters placed on the exit surface of a phantom, was characterized for e...

This paper presents an iterative autoregressive system parameter estimation algorithm in the presence of white observation noise. The algorithm is based on the parameter estimation bias correction approach. We use high order Yule–Walker equations, sequentially estimate the noise variance, and exploit these estimated variances for the bias correction. The improved performance of the proposed alg...