Search results for "Estimation"

Small area estimation with linear mixed models from unit-level panel and rotating panel data

2009

Video Scene analysis for a configurable hardware accelerator dedicated to Smart Camera

2012

International audience; According to the Center for Research and Prevention of Injuries report, fall-caused injuries of elderly people in UE- 27 are five times as frequent as other injury causes which reduce considerably their mobility and independence. Among the diverse applications of computer vision systems, object detection and event recognition are of the most prominent related recognition and motion analysis, that is, researchers had the idea to spread it in fall detection. The fall event, extracted automatically from the video scene represents itself, crucial information that can be used to alert emergency. In this context, visual information on the corresponding scene is highly impo…

A Channel-Aware Adaptive Modem for Underwater Acoustic Communications

2021

Acoustic underwater channels are very challenging, because of limited bandwidth, long propagation delays, extended multipath, severe attenuation, rapid time variation and large Doppler shifts. A plethora of underwater communication techniques have been developed for dealing with such a complexity, mostly tailoring specific applications scenarios which can not be considered as one-size-fits-all solutions. Indeed, the design of environment-specific solutions is especially critical for modulations with high spectral efficiency, which are very sensitive to channel characteristics. In this paper, we design and implement a software-defined modem able to dynamically estimate the acoustic channel c…

Joint second-order parameter estimation for spatio-temporal log-Gaussian Cox processes

2018

We propose a new fitting method to estimate the set of second-order parameters for the class of homogeneous spatio-temporal log-Gaussian Cox point processes. With simulations, we show that the proposed minimum contrast procedure, based on the spatio-temporal pair correlation function, provides reliable estimates and we compare the results with the current available methods. Moreover, the proposed method can be used in the case of both separable and non-separable parametric specifications of the correlation function of the underlying Gaussian Random Field. We describe earthquake sequences comparing several Cox model specifications.

SNP and SML estimation of univariate and bivariate binary–choice models

2008

We discuss the semi-nonparametric approach of Gallant and Nychka (1987, Econometrica 55: 363–390), the semiparametric maximum likelihood approach of Klein and Spady (1993, Econometrica 61: 387–421), and a set of new Stata commands for semiparametric estimation of three binary-choice models. The first is a univariate model, while the second and the third are bivariate models without and with sample selection, respectively. The proposed estimators are root-n consistent and asymptotically normal for the model parameters of interest under weak assumptions on the distribution of the underlying error terms. Our Monte Carlo simulations suggest that the efficiency losses of the semi-nonparametric a…

The optimisation of sampling design

2013

Elektroniskā versija nesatur pielikumus

Estimating Stress in Online Meetings by Remote Physiological Signal and Behavioral Features

2022

Work stress impacts people’s daily lives. Their well-being can be improved if the stress is monitored and addressed in time. Attaching physiological sensors are used for such stress monitoring and analysis. Such approach is feasible only when the person is physically presented. Due to the transfer of the life from offline to online, caused by the COVID-19 pandemic, remote stress measurement is of high importance. This study investigated the feasibility of estimating participants’ stress levels based on remote physiological signal features (rPPG) and behavioral features (facial expression and motion) obtained from facial videos recorded during online video meetings. Remote physiological sign…

Towards Robust Adaptive Least-Squares Parameter Estimation with Internal Feedback

1998

Abstract The new concepts of the ‘covariance matrix normalization’ and the ‘cascade’ structure of the adaptive least-squares estimator are shown to generalize and extend the use of internal information feedback in various robustness/alertness-oriented modifications to the standard ALS estimation algorithm. In the cascade estimation structure it is possible to ‘naturally’ stabilize, rather than maximize, the information matrix so that the covariance windup and blowup are effectively eliminated and the celebrated square root update of the covariance matrix is no longer needed Consequently, a new, ‘single-loop/cascade’ ALS MIMO estimation algorithm, enabling to effectively track both slow and …

Helsingin osa-alueiden työvoimatilastojen estimointi pienaluetekniikalla valtakunnallisesta työvoimatutkimuksesta

1997

Model selection using limiting distributions of second-order blind source separation algorithms

2015

Signals, recorded over time, are often observed as mixtures of multiple source signals. To extract relevant information from such measurements one needs to determine the mixing coefficients. In case of weakly stationary time series with uncorrelated source signals, this separation can be achieved by jointly diagonalizing sample autocovariances at different lags, and several algorithms address this task. Often the mixing estimates contain close-to-zero entries and one wants to decide whether the corresponding source signals have a relevant impact on the observations or not. To address this question of model selection we consider the recently published second-order blind identification proced…