In this paper we consider estimation and inference of common breaks in panel data models via adaptive group fused lasso. We consider two approaches — penalized least squares (PLS) for firstdifferenced models without endogenous regressors, and penalized GMM (PGMM) for first-differenced models with endogeneity. We show that with probability tending to one both methods can correctly determine the ...

In this letter, we propose an efficient method to improve the performance of voiced/unvoiced (V/UV) sounds decision for the selectable mode vocoder (SMV) of 3GPP2 using the Gaussian mixture model (GMM). We first present an effective analysis of the features and the classification method adopted in the SMV. And feature vectors which are applied to the GMM are then selected from relevant paramete...

A two-stage classifier is used to improve the classification performance between normal and pathological voices. A primary classification between normal and pathological voices is achieved by the Gaussian mixture model (GMM) log-likelihood scores. For samples that do not meet the thresholds for normal or disordered voice in the GMM, the final decision is made by a higher-order statistics (HOS)-...

The Journal of Economic Literature codes classification system (JEL) published by the American Association (AEA) is de facto standard for research literature in economics. JEL used to classify articles, dissertations, books, book reviews, and working papers EconLit, a database maintained AEA. Over time, it has evolved extended with over 850 subclasses. This paper reviews history development sys...

Innovation plays a crucial role in improving firm's performance. The relationship between innovation and productivity has been widely analysed during this decade across countries industries, generating important new findings. This study aims to provide an overall literature review on the of firms obtain comprehensive overview changing productivity. By reviewing existing empirical evidence, one ...

Long memory (long-term dependence) seems to be as widespread in financial time series as in nature. Inspired by the long memory property, Multi-fractal processes have recently been introduced as a new tool for modeling the stylized facts in financial time series. In this paper, we attempt to construct a bivariate multi-fractal model, and implement its estimation via both GMM and likelihood appr...

Bertschek and Lechner (1998) propose several variants of a GMM estimator based on the period specific regression functions for the panel probit model. The analysis is motivated by the complexity of maximum likelihood estimation and the possibly excessive amount of time involved in maximum simulated likelihood estimation. But, for applications of the size considered in their study, full likeliho...

Bertschek and Lechner (1998) propose several variants of a GMM estimator based on the period specific regression functions for the panel probit model. The analysis is motivated by the complexity of maximum likelihood estimation and the possibly excessive amount of time involved in maximum simulated likelihood estimation. But, for applications of the size considered in their study, full likeliho...

Language recognition with support vector machines and shifteddelta cepstral features has been an excellent performer in NISTsponsored language evaluation for many years. A novel improvement of this method has been the introduction of hybrid SVM/GMM systems. These systems use GMM supervectors as an SVM expansion for classification. In prior work, methods for scoring SVM/GMM systems have been int...