A classical problem in many radar and sonar applications is the adaptive detection/esti-mation of a given signal in the presence of zero mean Gaussian noise. Reed, Mallett, and Brennan (RMB) derived and analyzed an adaptive detection scheme where the noise adaptation and non-trivial nature of their analysis resulted from the use of a noise sample covariance matrix (SCM). The case now considered...

In this paper, a new control chart to monitor multi-binomial processes is first proposed based on a transformation method. Then, the maximum likelihood estimators of change points designed for both step changes and linear-trend disturbances are derived. At the end, the performances of the proposed change-point estimators are evaluated and are compared using some Monte Carlo simulation experimen...

In this note I will study the relationship between the conditional sum of squares (CSS) estimator of moving averages and the maximum likelihood (ML) estimator. I will show that the CSS estimator can be converted into the ML estimator via the use of the EM algorithm. A by-product of the EM algorithm is an expression for the likelihood function and the score. This argument generalizes to autoregr...

The main purpose of this paper is to introduce and study the behavior of minimum ϕ -divergence estimators as an alternative to the maximum-likelihood estimator in latent class models for binary items. As it will become clear below, minimum ϕ -divergence estimators are a natural extension of the maximum-likelihood estimator. The asymptotic properties of minimum ϕ -divergence estimators for laten...

Relatedness between individuals is central to many studies in genetics and population biology. A variety of estimators have been developed to enable molecular marker data to quantify relatedness. Despite this, no effort has been given to characterize the traditional maximum-likelihood estimator in relation to the remainder. This article quantifies its statistical performance under a range of bi...

This paper considers the three-parameter exponentiated Weibull family under type II censoring. It first graphically illustrates the shape property of the hazard function. Then, it proposes a simple algorithm for computing the maximum likelihood estimator and derives the Fisher information matrix. The latter one is represented through a single integral in terms of hazard function, hence it solve...

This paper introduces an iterative method to estimate the cointegrating vectors in the error correction models. The method provides the asymptotically efficient estimators for the cointegrating vectors if iterated once or more. If it is iterated until convergence, we may obtain the maximum likelihood estimator by Johansen. For all values of 1 ≤ k ≤ ∞, the k-step iterative estimators are asympto...

The maximum likelihood estimator of the Weibull shape parameter can be very biased. An estimator based on the modified profile likelihood is proposed and its properties are studied. It is shown that the new estimator is almost unbiased with relative bias being less than 1% in most of situations, and it is much more efficient than the regular MLE. The smaller the sample or the heavier of the cen...

The problem of parameter estimation of a single sinusoid with unknown offset in additive Gaussian noise is addressed. After deriving the linear prediction property of the noise-free signal, the maximum likelihood estimator for the frequency parameter is developed. The optimum estimator is relaxed according to the iterative quadratic maximum likelihood technique. The remaining parameters are the...

Abstrac t-The paper illustrates a method for simultaneous ADC and DAC linearity testing in a loopback scheme. The main features of the method are: (i) it is statistically nearly optimal, being based on a maximum likelihood estimator; (ii) it does not require prior knowledge neither of the ADC nonlinearity, nor of the DAC nonlinearity – both are simultaneously measured relying only on a constant...