Consider the semi-parametric linear regression model Y = ′X+ , where has an unknown distribution F0. The semi-parametric MLE
̃ of under this set-up is called the generalized semi-parametric MLE(GSMLE).Although the GSML estimation of the linear regression model is statistically appealing, it has never been attempted due to difficulties with obtaining the GSML estimates of and F until recent work...

Maximum likelihood estimation (MLE) methods are widely used for evolutionary tree. As evolutionary tree is not a smooth parameter, the consistency of its MLE has been a topic of debate. It has been noted without proof that the classical proof of consistency by Wald holds for the MLE of evolutionary tree. Other proofs of consistency under various models were also proposed. Here we will discuss s...

Estimating parameters in a mixture of normal distributions dates back to the 19th century when Pearson originally considered data of crabs from the Bay of Naples. Since then, many real world applications of mixtures have led to various proposed methods for studying similar problems. Among them, maximum likelihood estimation (MLE) and the continuous empirical characteristic function (CECF) metho...

The diffusion of the use of the learning virtual environments presents a great potential for the development of an application which meet the necessities in the education area. In view of the importance of a more dynamic application and that can adapt itself continuously to the students’ necessities, the “U-ALS” (Ubiquitous Adapted Learning System) was proposed and developed. This system was bu...

Maleless (mle) is essential in Drosophila melanogaster males both in somatic cells and in germ cells. In somatic cells mle is necessary for X-chromosome dosage compensation. The role of mle in the germline is unknown. We have analyzed the expression pattern and localization of MLE, the other MSLs and acetylated isoforms of histone H4 in male germ cells to address whether dosage compensation and...

The DNA repair protein Ku70 is a key player in chemoresistance to anticancer agents (e.g., etoposide) or radioresistance. The responses of different organs to radiation vary widely and likely depend on the cell population in the organs. Previously, we established and characterized Ku70-deficient murine lung epithelial (Ku70 -/- MLE) cells and found that these cells are more sensitive than Ku70 ...

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 a simpler “naive estimator.” Both types of estimators were studied by Jewell, van der Laan and Henneman [Biometrika (2003) 90 183–197], but little was known about their ...

The Pareto distribution is often used in many areas of economics to model the right tail of heavytailed distributions. However, the standard method of estimating the shape parameter (the Pareto index) of this distribution– the maximum likelihood estimator (MLE) – is non-robust, in the sense that it is very sensitive to extreme observations, data contamination or model deviation. In recent years...

Censored data sets are often encountered in water quality investigations and streamflow analyses. A Monte Carlo analysis examined the performance of three techniques for estimating the moments and quantiles of a distribution using censored data sets. These techniques include a lognormal maximum likelihood estimator (MLE), a logprobability plot regression estimator, and a new log-partial probabi...

A sparse parameter estimation method is proposed for identifying a stochastic monomolecular biochemical reaction network system. Identification of a reaction network can be achieved by estimating a sparse parameter matrix containing the reaction network structure and kinetics information. Stochastic dynamics of a biochemical reaction network system is usually modeled by a chemical master equati...