In this paper, we present a new maximum likelihood estimator (MLE) of carrier frequency offset for multicarrier signals in a frequency-selective Rayleigh fading channel. The proposed MLE is able to achieve wider estimation range of frequency offset with higher accuracy than previous blind approaches by exploiting the intrinsic structure of multicarrier signals. Simulations show that the estimat...

This paper considers the maximum likelihood estimation of factor models of high dimension, where the number of variables (N) is comparable with or even greater than the number of observations (T ). An inferential theory is developed. We establish not only consistency but also the rate of convergence and the limiting distributions. Five different sets of identification conditions are considered....

This paper is concerned with the study of the rate of convergence of the distribution of the maximum likelihood estimator (MLE) of parameter appearing linearly in the drift coefficient of two types of stochastic partial differential equations (SPDE’s).

This paper considers the non-parametric maximum likelihood estimator (MLE) for the joint distribution function of an interval-censored survival time and a continuous mark variable. We provide a new explicit formula for the MLE in this problem. We use this formula and the mark-specific cumulative hazard function of Huang & Louis (1998) to obtain the almost sure limit of the MLE. This result lead...

Delft University of Technology and Vrije Universiteit Amsterdam, University of Washington and University of Washington We study nonparametric estimation of the sub-distribution functions for current status data with competing risks. Our main interest is in the nonparametric maximum likelihood estimator (MLE), and for comparison we also consider the ‘naive estimator’ of Jewell, Van der Laan and ...

In practical applications of item response theory (IRT), item parameters are usually estimated first from a calibration sample. After treating these estimates as fixed and known, ability parameters are then estimated. However, the statistical inferences based on the estimated abilities can be misleading if the uncertainty of the item parameter estimates is ignored. Instead, estimated item param...

We study nonparametric estimation for current status data with competing risks. Our main interest is in the nonparametric maximum likelihood estimator (MLE), and for comparison we also consider a simpler “naive estimator.” Groeneboom, Maathuis and Wellner [Ann. Statist. (2008) 36 1031– 1063] proved that both types of estimators converge globally and locally at rate n1/3. We use these results to...

We study nonparametric estimation for current status data with competing risks. Our main interest is in the nonparametric maximum likelihood estimator (MLE), and for comparison we also consider a simpler 'naive estimator'. Groeneboom, Maathuis and Wellner [8] proved that both types of estimators converge globally and locally at rate n(1/3). We use these results to derive the local limiting dist...

| We formulate the problem of approximating a signal with a sum of chirped Gaussians, the so-called chirplets, under the framework of maximum likelihood estimation. For a signal model of one chirplet in noise, we formulate the maximum likelihood estimator (MLE) and compute the Cram er-Rao lower bound. An approximate MLE is developed, based on time-frequency methods, and is applied sequentially ...

This article considers the nonparametric maximum likelihood estimator (MLE) for the joint distribution function of an interval censored survival time and a continuous mark variable. We derive a new explicit formula for the MLE that has both computational and theoretical advantages. Using this formula and the mark specific cumulative hazard function of Huang & Louis (1998), we derive the almost ...