The least absolute deviation or L1 method is a widely known alternative to the classical least squares or L2 method for statistical analysis of linear regression models. Instead of minimizing the sum of squared errors, it minimizes the sum of absolute values of errors. Despite its long history and many ground-breaking works (cf. Portnoy and Koenker (1997) and references therein), the former has...

A robust, flexible system for tracking the point to point nonrigid motion of the left ventricular (LV) endocardial wall in image sequences has been developed. This system is unique in its ability to model motion trajectories across multiple frames. The foundation of this system is an adaptive transversal filter based on the recursive least-squares algorithm. This filter facilitates the integrat...

[1] This is a study to quantify U.S. wind power at 80 m (the hub height of large wind turbines) and to investigate whether winds from a network of farms can provide a steady and reliable source of electric power. Data from 1327 surface stations and 87 soundings in the United States for the year 2000 were used. Several methods were tested to extrapolate 10-m wind measurements to 80 m. The most a...

INTRODUCTION Phase-contrast magnetic resonance imaging has the ability to accurately measure blood flow and myocardial velocities in the human body. Unwanted spatially varying phase offsets are, however, always present and may deteriorate the measurements significantly. Some of these phase offsets can be estimated based on the pulse sequence (1), but effects caused by eddy currents are more dif...

In this paper, a computationally very efficient algorithm for direction of arrival (DOA) as well as range parameter estimation is proposed for near-field narrowband nonstationary accelerated moving sources. The proposed algorithm based on the local polynomial approximation (LPA) beamformer, which proves its efficiency with far-field applications. The LPA estimates the instantaneous values of th...

We assessed the ability of several penalized regression methods for linear and logistic models to identify outcome-associated predictors and the impact of predictor selection on parameter inference for practical sample sizes. We studied effect estimates obtained directly from penalized methods (Algorithm 1), or by refitting selected predictors with standard regression (Algorithm 2). For linear ...

Partial least squares (PLS) regression is commonly used for multivariate calibration of instruments. Because of the need to know the quality of the prediction in a specific unknown sample and the lack of theory, an 'empirically found formula' to express the uncertainty is utilized in The Unscrambler II software, the de-facto standard in computer software for PLS. In this critique the formula is...

We report here a refinement of the potential energy surface for the electronic ground state of the H2S molecule in a least-squares fit to experimental spectroscopic data. The calculations are carried out by combining an exact kinetic energy (EKE) approach to the calculation of the rotation–vibration energies of a triatomic molecule with the MORBID approach, which employs an approximate kinetic ...

Several indices, including the normalized difference vegetation index (NDVI), normalized difference build-up index (NDBI), and normalized difference water index (NDWI), were retrieved from the Landsat 5 Thematic Mapper (TM) images, and the land surface temperature (LST) was reversed by the thermal radiation transfer model. Next, with the help of the thermal field variance index from LST, charac...