A recent short communication [1] showed that an orthogonal subspace projection (OSP) classifier developed for hyperspectral image classification in [2] was equivalent to a maximum likelihood estimator (MLE) resulting from a standard method of linear unmixing. It further concluded that the MLE subsumed the OSP classifier in spite of a constant difference in their magnitudes. Coincidentally, the ...

Direct blast, a strong interference in bistatic sonar, is difficult to suppress because of multipath propagation for blasts and signals. A generalized likelihood ratio test (GLRT)-based detection scheme the frequency domain received signals was proposed, unknown parameters were estimated using maximum estimate (MLE) under environment. The distributions statistic detectors known noise power give...

In this article, we have proposed a new distribution having three parameters using half Cauchy family of called Half-Cauchy Exponential extension Distribution. The statistical properties as well different characteristics like the hazard rate function (HRF), probability density (PDF), cumulative (CDF), quantile function, skewness, and kurtosis are discussed. estimated by least-square estimation ...

♦ parameter space-Ω = {all θ} ♦ estimator-a random variable (or vector) ♦ estimate-a value (vector) derived from a realization ♦ (log)-likelihood function-n i=1 f (x i ; θ). ♦ maximum likelihood estimator (estimate)[mle]) is called an unbiased estimator of θ. Otherwise, it is said to be biased. ♦ parameter estimation by method of moments. Example 1: mle for the mean and variance of a random sam...

We have observed an interesting, yet unexplained, phenomenon: Semidefinite programming (SDP) based relaxations of maximum likelihood estimators (MLE) tend to be tight in recovery problems with noisy data, even when MLE cannot exactly recover the ground truth. Several results establish tightness of SDP based relaxations in the regime where exact recovery from MLE is possible. However, to the bes...

With large numbers of hydroxyl groups, the trimethylsilyl derivatives become too large in mass for the range of many quadrupole mass spectrometers, so methylation is used. However, this would cause problems in structural elucidation since those compounds in which demethylation of the methoxyl or dimethylamino group had taken place would be remethylated, thus obscuring these demethylating proces...

BACKGROUND Stress is a consequence of different types of external demands, most of which have been shown to be associated with increased risk of ischaemic heart disease (IHD), but whether accumulation of stressors over a life-course results in additional risk of IHD remains unknown. This study investigates the impact of major life events (MLE) in childhood, adulthood and at work, singly and acc...

Maximum Likelihood Estimation (MLE) is a widely used statistical estimation method. In this lecture, we will study its properties: efficiency, consistency and asymptotic normality. MLE is a method for estimating parameters of a statistical model. Given the distribution of a statistical model f(y ; θ) with unkown deterministic parameter θ, MLE is to estimate the parameter θ by maximizing the pro...

This paper studies the estimation of high-dimensional, discrete, possibly sparse, mixture models in context topic models. The data consists observed multinomial counts p words across n independent documents. In models, p×n expected word frequency matrix is assumed to be factorized as a p×K word-topic A and K×n topic-document T. Since columns both matrices represent conditional probabilities bel...

We propose a neural encoder-decoder model with reinforcement learning (NRL) for grammatical error correction (GEC). Unlike conventional maximum likelihood estimation (MLE), the model directly optimizes towards an objective that considers a sentence-level, task-specific evaluation metric, avoiding the exposure bias issue in MLE. We demonstrate that NRL outperforms MLE both in human and automated...