Multivariate linear regression

Introduction  Pulse pressure (PP) has been reported as an independent predictor of cardiovascular mortality in hemodialysis patients. In this study, we aimed to investigate association of PP with echocardiographic and vascular structural changes such as atherosclerosis and arterial calcifications in HD patients. Patients and methods  In this cross-sectional study, 108 chronic hemodialysis patients (49 male, 59 female, mean age: 46 ± 13 years) were included.

Varieties of lottery games are played regularly in more than half of the world’s countries. When considering the probability of winning a lottery jackpot, we have a sense of the illogicality in buying a lottery ticket. This begs the question, why do people buy lottery products? This paper investigates the socio-economic and demographic features that help to explain the behavioural

This article introduces the sparse group fused lasso (SGFL) as a statistical framework for segmenting sparse regression models with multivariate time series. To compute solutions of the SGFL, a nonsmooth and nonseparable convex program, we develop a hybrid optimization method that is fast, requires no tuning parameter selection, and is guaranteed to converge to a global minimizer. In numerical experiments, the hybrid method compares favorably to state-of-the-art techniques with respect to computation time and numerical accuracy; benefits are particularly substantial in high dimension. The method's statistical performance is satisfactory in recovering nonzero regression coefficients and excellent in change point detection. An application to air quality data is presented. The hybrid method is implemented in the R package sparseGFL available on the author's Github page.

In today's connected world, the availability of fast Internet access and penetration of smart-phones has created an opportunity for the emerging of new telecom services. Similarly, in Ethiopia, the improvement of technology brought a change from the traditional services to more advanced communication like video streaming service. To ensure whether the customers have satisfied for a given service or not, capturing user Quality of Experience (QoE) is important. Traditionally, Internet Service Providers (ISP)s monitor the network performance by collecting network key performance indicators without involving users' perception. However, user-perceived QoE estimation is multidimensional, which is affected by different influencing factors. So, estimating user-centric QoE based on Network-level QoS (NQoS) remains challenging tasks for ISPs. Yet, QoE assessment model for video streaming services that map Quality of Service (QoS) to QoE concerning users' perception has not been performed in Ethiopia. This thesis proposes video streaming QoE assessment models using machine learning techniques to estimate user-perceived experience in the Long-Term Evolution (LTE) network. The model predicts perceived QoE in a Mean Opinion Score (MOS), by evaluating NQoS, Application-level QoS (AQoS) and contextually formulated survey questionnaire. The models take NQoS metrics such as upload bit rate and download bit rate in Megabits Per Second (Mb/s), latency and jitter in milliseconds (ms), and packet loss in percentage. Content-type and resolution also considered from the application level. Contrary to existing models for QoE prediction, the proposed model gives a good estimation of the perceived quality with a minimum Mean Squared Error (MSE) of 7.74%; and Pearson and Spearman correlations of 97.94% and 97.43%, corresponding to the measured QoE. The result obtained from the model shows that the average MOS value is 2.79, which is below the recommended one. Accordingly, the proposed model allows ISP to monitor the perceived QoE level accurately.

Snow water equivalent (SWE) is a key param-eter in hydrological cycle, and information on regional SWE is required for various hydrological and meteorolog-ical applications, as well as for hydropower production and flood forecasting. This study compares the snow depth ...

BACKGROUND: Remote sensing technology provides detailed spectral and thermal images of the earth's surface from which surrogate ecological indicators of complex processes can be measured. METHODS: Remote sensing data were overlaid onto georeferenced entomological and human ecological data randomly sampled during April and May 2001 in the cities of Kisumu (population asymptotically equal to 320,000) and Malindi (population asymptotically equal to 81,000), Kenya. Grid cells of 270 meters x 270 meters were used to generate spatial sampling units for each city for the collection of entomological and human ecological field-based data. Multispectral Thermal Imager (MTI) satellite data in the visible spectrum at five meter resolution were acquired for Kisumu and Malindi during February and March 2001, respectively. The MTI data were fit and aggregated to the 270 meter x 270 meter grid cells used in field-based sampling using a geographic information system. The normalized difference ve...

Scaling laws provide a simple yet meaningful representation of the dominant factors of complex engineering systems, and thus are well suited to guide engineering design. Current methods to obtain useful models of complex engineering systems are typically ad-hoc, tedious, and time consuming. Here we present an algorithm that obtains a scaling law in the form of a power law from

Peer-based prevention programs for homeless youth are complicated by the potential for reinforcing high-risk behaviors among participants. The goal of this study is to understand how homeless youth could be linked to positive peers in prevention programming by understanding where in social and physical space positive peers for homeless youth are located, how these ties are associated with substance use,

Background  Latinos in the United States have a higher prevalence of type 2 diabetes than non-Latino whites, even after controlling for adiposity. Decreased adiponectin is associated with insulin resistance and predicts T2DM, and therefore may mediate this ethnic difference. We compared total and high-molecular-weight (HMW) adiponectin in Latino versus white individuals, identified factors associated with adiponectin in each ethnic group, and