Search results for " estimators"

An adaptive approach to learning the preferences of users in a social network using weak estimators

2012

Published version of an article in the journal: Journal of Information Processing Systems. Also available from the publisher at: http://dx.doi.org/10.3745/JIPS.2012.8.2.191 - Open Access Since a social network by definition is so diverse, the problem of estimating the preferences of its users is becoming increasingly essential for personalized applications, which range from service recommender systems to the targeted advertising of services. However, unlike traditional estimation problems where the underlying target distribution is stationary; estimating a user's interests typically involves non-stationary distributions. The consequent time varying nature of the distribution to be tracked i…

Data granularity in mid-year life table construction

2020

[EN] Life tables have a substantial influence on both public pension systems and life insurance policies. National statistical agencies construct life tables from death rate estimates (𝑚���𝑥���), or death probabilities (𝑞���𝑥��� ), after applying various hypotheses to the aggregated figures of demographic events (deaths, migrations and births). The use of big data has become extensive across many disciplines, including population statistics. We take advantage of this fact to create new (more unrestricted) mortality estimators within the family of period-based estimators, in particular, when the exposed-to-risk population is computed through mid-year population estimates. We use actual d…

Advanced Motion Control in Induction Motor Systems - Modelling, Analysis and Control

Using a unified notation, this thesis collects and discusses the most important steps and issues in the design of estimation and control algorithms for induction motors. It contains many estimation and control algorithms. Their stability is analyzed and their performance is illustrated by simulations and experiments on the same induction motor. An intense and challenging collective research effort is carefully documented and analyzed, with the aim of providing and clarifying the basic intuition and tools required in the analysis and design of nonlinear feedback control algorithms. This material should be of specific interest to engineers who are engaged in the design of control algorithms f…

A fast and recursive algorithm for clustering large datasets with k-medians

2012

Clustering with fast algorithms large samples of high dimensional data is an important challenge in computational statistics. Borrowing ideas from MacQueen (1967) who introduced a sequential version of the $k$-means algorithm, a new class of recursive stochastic gradient algorithms designed for the $k$-medians loss criterion is proposed. By their recursive nature, these algorithms are very fast and are well adapted to deal with large samples of data that are allowed to arrive sequentially. It is proved that the stochastic gradient algorithm converges almost surely to the set of stationary points of the underlying loss criterion. A particular attention is paid to the averaged versions, which…

On the Ambiguous Consequences of Omitting Variables

2015

This paper studies what happens when we move from a short regression to a long regression (or vice versa), when the long regression is shorter than the data-generation process. In the special case where the long regression equals the data-generation process, the least-squares estimators have smaller bias (in fact zero bias) but larger variances in the long regression than in the short regression. But if the long regression is also misspecified, the bias may not be smaller. We provide bias and mean squared error comparisons and study the dependence of the differences on the misspecification parameter.

On the ambiguous consequences of omitting variables

2015

This paper studies what happens when we move from a short regression to a long regression (or vice versa), when the long regression is shorter than the data-generation process. In the special case where the long regression equals the data-generation process, the least-squares estimators have smaller bias (in fact zero bias) but larger variances in the long regression than in the short regression. But if the long regression is also misspecified, the bias may not be smaller. We provide bias and mean squared error comparisons and study the dependence of the differences on the misspecification parameter.

Food predictability determines space use of endangered vultures: implications for management of supplementary feeding.

2013

Understanding space use of free-living endangered animals is key to inform management decisions for conservation planning. Like most scavengers, vultures have evolved under a context of unpredictability of food resources (i.e. exploiting scattered carcasses that are intermittently available). However, the role of predictable sources of food in shaping spatial ecology of vultures has seldom been studied in detail. Here, we quantify the home range of the Egyptian vulture (Neophron percnopterus), a long-lived raptor which has experienced severe population decline throughout its range and is qualified as endangered worldwide. To this end six adults were tracked by satellite telemetry in Spain d…

Teacher shortages, teacher contracts and their effect on education in Africa

2010

1001; To enhance primary enrolment rates, many African countries have launched large teacher recruitment programmes in recent years. Given tight budgetary constraints, teachers are no longer employed in civil service positions, but on the basis of (fixed term) contracts typically implying considerably lower salaries and a sharply reduced amount of professional training. We analyse the effect of this change on educational quality in Niger, Togo and Mali, on the basis of very informative data, which are comparable across these countries. We use a variety of estimation techniques, including a non-parametric estimation of quantile treatment effects. Our results demonstrate that contract teacher…

Network Capacity Estimators Predicting QoE in HTTP Adaptive Streaming

2022

The aim of adaptive HTTP streaming technology is preserving the best possible video streaming quality for viewers in heterogeneous network conditions. This can be achieved by making multiple quality versions of the video available. Switching between versions during playback should be imperceptible and fluent. The decision about quality-level switching is typically based on network capacity estimation and buffer occupancy, which predict the risk of stalling. Since quality-level switching and stalling are directly evident to the user, they are often classified as influence factors of quality of experience (QoE). In this paper, we observe different network capacity estimators and buffer behavi…