This paper presents an indoor broadband ultrasonic system for estimation of a mobile device’s 3-D location and three-axis orientation using beacons. It presents the first implementation and characterization of a real ...
Partial derivatives of the negative exponential, monomolecular, Mitcherlich, Gompertz,
logistic, Chapman-Richards, von Bertalanffy, Weibull and the Richard’s nonlinear
growth models are presented. The application of these ...
In this paper we provide an analytical review of previous estimates of the rate of return on schooling investments and measure how these estimates vary by country, over time, and by estimation method. We find evidence of ...
Kernel density estimators are a non-parametric method of
estimating the probability density function of sample data. In this paper, the
method is applied to find characteristic maximum daily truck weights on
highway ...
We introduce two simple new variants of the Jackknife Instrumental Variables (JIVE) estimator for overidentified linear models and show that they are superior to the existing JIVE estimator, significantly
improving on its ...
In terms of risk measurement, probability and quantile risk estimation have developed enormously in the past decade, from value-at-risk measures to coherent measures such as expected shortfall. These measures allow an ...
Herein a two stage Kalman filter based algorithm is proposed for processing of Inertial Measurement Unit (IMU) data to obtain accurate position estimation over a short period of time. The proposed algorithm uses a novel ...
This study presents nonparametric estimates of spectral risk measures (SRM)
applied to long and short positions in five prominent equity futures contracts. It
also compares these to estimates of two popular alternative ...
We apply a new estimator to the measurement of the economic returns to education. We control for endogenous education, unobserved ability and measurement error using only the natural heteroscedasticty of wages and education ...