We applied a variety of parametric and non-parametric machine learning models to predict the probability distribution of rainfall based on 1M training examples over a single year across several U.S. states. Our top performing model based on a squared loss objective was a cross-validated parametric k-nearest-neighbor predictor that took about six days to compute, and was competitive in a world-w...

The motivation behind the idea of product focused process improvement is to make a process improvement program address certain product quality features in an explicit manner. The PROFES methodology [PROFES (2001)] describes such an improvement program through the notion of a PPD (Product-Process Dependency) repository. A PPD model tells which improvement action will result in the improvement of...

In various contexts, animals rely on acoustic signals to differentiate between conspecifics. Currently, studies examining vocal signatures use two main approaches. In the first approach, researchers search for acoustic characteristics that have the potential to be individual specific. This approach yields information on variation in signal parameters both within and between individuals and gene...

For this study, empirical data on the thermal comfort parameters (i.e. room space temperature, velocity and relative humidity) was collected for the computation of the PMV and PPD thermal comfort index for the three flat types. The study shows that wind ventilation has a great effect on the interior comfort condition. This is evident from the diurnal variations of PMV values. Majority of the da...

Corresponding Author: Junqiu Wang AVIC Intelligent Measurement, Aviation Industry Cooperation China, Beijing, China Email: [email protected] Abstract: We present a fragment-based tracking algorithm that considers appearance information characterized by a non-parametric distribution and spatial information described by a parametric representation. We segment an input object into several fragm...

A system of multivariate semiparametric nonlinear time series models is studied with possible dependence structures and nonstationarities in the parametric and nonparametric components. The parametric regressors may be endogenous while the nonparametric regressors are assumed to be strictly exogenous. The parametric regressors may be stationary or nonstationary and the nonparametric regressors ...

A system of vector semiparametric nonlinear time series models is studied with possible dependence structures and nonstationarities in the parametric and nonparametric components. The parametric regressors may be endogenous while the nonparametric regressors are strictly exogenous. The parametric regressors may be stationary or nonstationary and the nonparametric regressors are nonstationary ti...

Often the probability of responding depends directly on the outcome value. This case can be treated by postulating a parametric model for the distribution of the outcomes before nonresponse and a model for the response mechanism. The two models define a parametric model for the joint distribution of the outcomes and response indicators, and therefore the parameters of these models can be estima...

capacity of a road facility as an important characteristic in transportation and traffic studies is defined as the maximum rate of flow that could be held by that facility, which has been supposed to have a constant and certain value. this assumption, although necessary for most traffic studies, has also caused some problems, like that of demand exceeding capacity in many road facilities. resea...

Constructing ultrasound statistical parametric images by using a sliding window is a widely adopted strategy for characterizing tissues. Deficiency in spatial resolution, the appearance of boundary artifacts, and the prerequisite data distribution limit the practicability of statistical parametric imaging. In this study, small-window entropy parametric imaging was proposed to overcome the above...