Results 11  20
of
2,564
Rangebased estimation of stochastic volatility models
, 2002
"... We propose using the price range in the estimation of stochastic volatility models. We show theoretically, numerically, and empirically that rangebased volatility proxies are not only highly efficient, but also approximately Gaussian and robust to microstructure noise. Hence rangebased Gaussian qu ..."
Abstract

Cited by 223 (19 self)
 Add to MetaCart
We propose using the price range in the estimation of stochastic volatility models. We show theoretically, numerically, and empirically that rangebased volatility proxies are not only highly efficient, but also approximately Gaussian and robust to microstructure noise. Hence rangebased Gaussian
Characterizing Reference Locality in the WWW
, 1996
"... As the World Wide Web (Web) is increasingly adopted as the infrastructure for largescale distributed information systems, issues of performance modeling become ever more critical. In particular, locality of reference is an important property in the performance modeling of distributed information sy ..."
Abstract

Cited by 220 (21 self)
 Add to MetaCart
of requests arriving at Web servers. We show that simple models based only on document popularity (likelihood of reference) are insufficient for capturing either temporal or spatial locality. Instead, we rely on an equivalent, but numerical, representation of a reference stream: a stack distance trace. We
Monte Carlo maximum likelihood estimation for nonGaussian state space models
, 1997
"... State space models are considered for observations which have nonGaussian distributions. We obtain accurate approximations to the loglikelihood for such models by Monte Carlo simulation. Devices are introduced which improve the accuracy of the approximations and which increase computational efficie ..."
Abstract

Cited by 126 (22 self)
 Add to MetaCart
efficiency. The loglikelihood function is maximised numerically to obtain estimates of the unknown hyperparameters. Standard errors of the estimates due to simulation are calculated. Details are given for the important special cases where the observations come from an exponential family distribution
Restricted maximum likelihood estimation for animal models using derivatives of the likelihood
, 1996
"... A Restricted Maximum Likelihood procedure is described to estimate variance components for a univariate mixed model with two random factors. An EMtype algorithm is presented with a reparameterisation to speed up the rate of convergence. Computing strategies are outlined for models common to the ana ..."
Abstract

Cited by 84 (21 self)
 Add to MetaCart
A Restricted Maximum Likelihood procedure is described to estimate variance components for a univariate mixed model with two random factors. An EMtype algorithm is presented with a reparameterisation to speed up the rate of convergence. Computing strategies are outlined for models common
Blind Separation of Mixture of Independent Sources Through a Maximum Likelihood Approach
 In Proc. EUSIPCO
, 1997
"... In this paper we propose two methods for separating mixtures of independent sources without any precise knowledge of their probability distribution. They are obtained by considering a maximum likelihood solution corresponding to some given distributions of the sources and relaxing this assumption af ..."
Abstract

Cited by 123 (8 self)
 Add to MetaCart
In this paper we propose two methods for separating mixtures of independent sources without any precise knowledge of their probability distribution. They are obtained by considering a maximum likelihood solution corresponding to some given distributions of the sources and relaxing this assumption
Pictorial structures revisited: People detection and articulated pose estimation
 In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009
, 2009
"... Nonrigid object detection and articulated pose estimation are two related and challenging problems in computer vision. Numerous models have been proposed over the years and often address different special cases, such as pedestrian detection or upper body pose estimation in TV footage. This paper sh ..."
Abstract

Cited by 211 (17 self)
 Add to MetaCart
Nonrigid object detection and articulated pose estimation are two related and challenging problems in computer vision. Numerous models have been proposed over the years and often address different special cases, such as pedestrian detection or upper body pose estimation in TV footage. This paper
Stochastic Completion Fields: A Neural Model of Illusory Contour Shape and Salience
 Neural Computation
, 1995
"... We describe an algorithm and representation level theory of illusory contour shape and salience. Unlike previous theories, our model is derived from a single assumption namely, that the prior probability distribution of boundary completion shape can be modeled by a random walk in a lattice whose ..."
Abstract

Cited by 210 (14 self)
 Add to MetaCart
points are positions and orientations in the image plane (i.e., the space which one can reasonably assume is represented by neurons of the mammalian visual cortex). Our model does not employ numerical relaxation or other explicit minimization, but instead relies on the fact that the probability that a
Maximum Likelihood Estimation for Filtering Thresholds
 IN PROCEEDINGS OF THE 24TH ANNUAL INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL
, 2001
"... Information filtering systems based on statistical retrieval models usually compute a numeric score indicating how well each document matches each profile. Documents with scores above profilespecific dissemination thresholds are delivered. An optimal dissemination threshold is one that maximizes a ..."
Abstract

Cited by 59 (7 self)
 Add to MetaCart
Information filtering systems based on statistical retrieval models usually compute a numeric score indicating how well each document matches each profile. Documents with scores above profilespecific dissemination thresholds are delivered. An optimal dissemination threshold is one that maximizes
On the Likelihood of an Equivalence
"... Abstract. Coreferences are traditionally used when integrating data from different datasets. This approach has various benefits such as fault tolerance, ease of integration and traceability of provenance; however, it often results in the problem of entity consolidation, i.e., of objectively stating ..."
Abstract
 Add to MetaCart
been observed that to indicate the likelihood of an equivalence one could use a numerically weighted measure, but the real hard questions of where precisely these values come from arises. We propose and discuss an answer to this question.
Likelihood Ratio Gradient Estimation For Stochastic Recursions
 Communications of the ACM
, 1995
"... . In this paper, we develop mathematical machinery for verifying that a broad class of general state space Markov chains reacts smoothly to certain types of perturbations in the underlying transition structure. Our main result provides conditions under which the stationary probability measure of an ..."
Abstract

Cited by 77 (8 self)
 Add to MetaCart
of an ergodic Harris recurrent Markov chain is differentiable in a certain strong sense. The approach is based on likelihood ratio "changeofmeasure" arguments, and leads directly to a "likelihood ratio gradient estimator" that can be computed numerically. Keywords: Harris recurrent Markov
Results 11  20
of
2,564