This article concerns the study of the asymptotic properties of the maximum likelihood estimator (MLE) for the general hidden semi-Markov model (HSMM) with backward recurrence time dependence. By transforming the general HSMM into a general hidden Markov model, we prove that under some regularity conditions, the MLE is strongly consistent and asymptotically normal. We also provide useful expres...

Recent research has demonstrated that the rotor angle stability can be assessed by identifying the sign of the system’s maximal Lyapunov exponent (MLE). A positive (negative) MLE implies unstable (stable) rotor angle dynamics. However, because the MLE may fluctuate between positive and negative values for a long time after a severe disturbance, it is difficult to determine the system stability ...

OBJECTIVES The Mikania laevigata extract (MLE) (popularly known in Brazil as "guaco") possesses anti-inflammatory properties. In the present study we tested the effects of MLE in a periodontitis experimental model in rats. We also investigated possible mechanisms underlying such effects. MATERIAL AND METHODS Periodontal disease was induced by a ligature placed around the mandibular first mola...

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 ...

♦ 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...

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...