A general simulation procedure is described to validate model fitting algorithms for complex likelihood functions that are utilized in periodic cancer screening trials. Although screening programs have existed for a few decades, there are still many unsolved problems, such as how age or hormone affects the screening sensitivity, the sojourn time in the preclinical state, and the transition prob...

ÐImage matching applications such as tracking and stereo commonly use the sum-of-squared-difference (SSD) measure to determine the best match. However, this measure is sensitive to outliers and is not robust to template variations. Alternative measures have also been proposed that are more robust to these issues. We improve upon these using a probabilistic formulation for image matching in term...

In the research literature, maximum likelihood principles were applied to stereo matching by altering the stereo pair so that the difference would have a Gaussian distribution. Here in this paper we present a novel method of applying maximum likelihood to stereo matching. In our approach, we measure the real noise distribution from a training set, and then construct a new metric which we denote...

We present a novel method to reconstruct the mass distribution of galaxy clusters from their gravitational lens effect on background galaxies. The method is based on a least-x 2 fit of the two-dimensional gravitational cluster potential. The method combines information from shear and magnification by the cluster lens and is designed to easily incorporate possible additional information. We desc...

– Maximum-likelihood methods are applied to the problem of absorption tomography. The reconstruction is done with the help of an iterative algorithm. We show how the statistics of the illuminating beam can be incorporated into the reconstruction. The proposed reconstruction method can be considered as a useful alternative in the extreme cases where the standard ill-posed direct-inversion method...

This module introduces the maximum likelihood estimator. We show how the MLE implements the likelihood principle. Methods for computing th MLE are covered. Properties of the MLE are discussed including asymptotic e ciency and invariance under reparameterization. The maximum likelihood estimator (MLE) is an alternative to the minimum variance unbiased estimator (MVUE). For many estimation proble...

We present a stochastic model of suprathreshold perceptual differences based on difference measurement. We develop a maximum likelihood difference scaling (MLDS) method for estimating its parameters and evaluate the reliability and distributional robustness of the fitting method. We also describe a method for testing whether the difference measurement model is appropriate as a description of hu...

The method of maximum likelihood (ML), introduced by Fisher (1921), is widely used in human and quantitative genetics and we draw upon this approach throughout the book, especially in Chapters 13–16 (mixture distributions) and 26–27 (variance component estimation). Weir (1996) gives a useful introduction with genetic applications, while Kendall and Stuart (1979) and Edwards (1992) provide more ...

Blind recognition of communication parameters is a research topic of high importance for both military and civilian communication systems. Numerous studies about carrier frequency estimation, modulation recognition as well as channel identification are available in literature. This paper deals with the blind recognition of the space–time block coding (STBC) scheme used in multiple-input–multipl...

This paper explores the use of ALOS (Advanced Land Observing Satellite) PALSARL-band (Phased Array type L-band Synthetic Aperture Radar) and RADARSAT-2 C-band data for land-cover classification in a tropical moist region. Transformed divergence was used to identify potential textural images which were calculated with the gray-level co-occurrence matrix method. The standard deviation of selected...