We present a new approach to stochastic modeling of constraintbased grammars that is based on loglinear models and uses EM for estimation from unannotated data. The techniques are applied to an LFG grammar for German. Evaluation on an exact match task yields 86% precision for an ambiguity rate of 5.4, and 90% precision on a subcat frame match for an ambiguity rate of 25. Experimental comparison...

We analyse maintenance cost data for Swedish railway infrastructure in relation to traffic volumes and other characteristics, and separate the cost impact from passenger and freight trains. Lines with mixed passenger and freight traffic, and dedicated freight lines are analysed separately using both log-linear and Box-Cox regression models. We find that for mixed lines, the Box-Cox specificatio...

This study estimates the impact of London’s successful 2012 summer Olympics bid on property prices. Using a self-constructed dataset of a sample of property transactions, we estimate a semilogarithmic hedonic model for Greater London. Applying a difference-in-differences estimator, we find that properties in the host boroughs are sold between 2.1 and 3.3 percent higher, depending on the definit...

This is cross sectional study based on 304 households (couples) with wives age less than 48 years, chosen from urban locality (city Lahore). Fourteen religious, demographic and socioeconomic factors of categorical nature like husband education, wife education, husband’s monthly income, occupation of husband, household size, husband-wife discussion, number of living children, desire for more chi...

Computer transaction log analysis comprises the modeling of patterns of machine–user transactions. Due to the web-like structure of the Internet, Interactions can be represented in a three-dimensional, origin–destination–time flow/transaction matrix. Loglinear models are used to model these transactions in terms of their time, origin and destination components and to detect the signature and st...

This paper reviews several common challenges encountered in statistical analyses of epidemiological data for epidemiologists. We focus on the application of linear regression, multivariate logistic regression, and log-linear modeling to epidemiological data. Specific topics include: (a) deletion of outliers, (b) heteroscedasticity in linear regression, (c) limitations of principal component ana...

Logistic regression is a technique to map the input feature to the posterior probability for a binary class. The optimal parameter of regression function is obtained by maximizing log likelihood of training data. In this report, we implement two optimization techniques 1) stochastic gradient decent (SGD); 2) limited-memory BroydenFletcherGoldfarbShanno (L-BFGS) to optimize the log likelihood fu...

In this paper, we propose a nonlinear regression method for speech enhancement, whose idea approximates the log spectra of clean speech with the inputs of the log spectra of noisy speech and estimated noise. We compared both subjective and objective assessments on regression-enhanced speech to those obtained through spectral subtraction (SS) and short-time spectral amplitude (STSA) methods. Our...