Suppose the p-variate random vector W, partitioned into q variables W-1 and p - q variables W-2, follows a multivariate normal mixture distribution. If the investigator is mainly interested in estimation of the parame...
详细信息
Suppose the p-variate random vector W, partitioned into q variables W-1 and p - q variables W-2, follows a multivariate normal mixture distribution. If the investigator is mainly interested in estimation of the parameters of the distribution of W-1, there are two possibilities: (1) use only the data on W, for estimation, and (2) estimate the parameters of the p-variate mixture distribution, and then extract the estimates of the marginal distribution of W-1. In this article we study the choice between these two possibilities mainly for the case of two mixture components with Identical covariance matrices. We find the asymptotic distribution of the linear discriminant function coefficients using the work of Efron (1975) and O'Neill (1978), and give a Wald-test for redundancy of W-2. A simulation study gives further insights into conditions under which W-2 should be used in the analysis: in summary, the inclusion of W-2 seems justified if Delta(2.1), the Mahalanobis distance between the two component distributions based on the conditional distribution of W-2 given W-1, is at least 2.
This article describes a new algorithm for exact computation of the observed information matrix in hidden Markov models that may be performed in a single pass through the data. The score vector and log-likelihood are ...
详细信息
This article describes a new algorithm for exact computation of the observed information matrix in hidden Markov models that may be performed in a single pass through the data. The score vector and log-likelihood are computed in the same pass. The new algorithm is derived from the forward-back ward algorithm traditionally used to evaluate the likelihood in hidden Markov models. Our result is discussed in the context of previous approaches that have been used to obtain approximate standard errors of parameter estimates in these models. Implications for parameter estimation are also discussed. An application of the proposed methods to rainfall occurrence data is provided.
The em algorithm is used to track moving objects as clusters of pixels significantly different from the corresponding pixels in a reference image. The underlying cluster model is Gaussian in image space, but not in gr...
详细信息
The em algorithm is used to track moving objects as clusters of pixels significantly different from the corresponding pixels in a reference image. The underlying cluster model is Gaussian in image space, but not in grey-level difference distribution. The generative model is used to derive criteria for the elimination and merging of clusters, while simple heuristics are used for the initialisation and splitting of clusters. The system is competitive with other tracking algorithms based on image differencing. (C) 2002 Elsevier Science B.V. All rights reserved.
This paper casts the problem of perceptual grouping into an evidence combining setting using the apparatus of the em algorithm. We are concerned with recovering a perceptual arrangement graph for line-segments using e...
详细信息
This paper casts the problem of perceptual grouping into an evidence combining setting using the apparatus of the em algorithm. We are concerned with recovering a perceptual arrangement graph for line-segments using evidence provided by a raw perceptual grouping field. The perceptual grouping process is posed as one of pairwise relational clustering. The task is to assign line-segments (or other image tokens) to clusters in which there is strong relational affinity between token pairs. The parameters of our model are the cluster memberships and the pairwise affinities or link-weights for the nodes of a perceptual relation graph. Commencing from a simple probability distribution for these parameters, we show how they may be estimated using the apparatus of the em algorithm. The new method is demonstrated on line-segment grouping problems where it is shown to outperform a non-iterative eigenclustering method. (C) 2002 Elsevier Science B.V. All rights reserved.
In this paper, we study the use of continuous-time hidden Markov models (CT-HMMs) for network protocol and application performance evaluation. We develop an algorithm to infer the CT-HMM from a series of end-to-end de...
详细信息
In this paper, we study the use of continuous-time hidden Markov models (CT-HMMs) for network protocol and application performance evaluation. We develop an algorithm to infer the CT-HMM from a series of end-to-end delay and loss observations of probe packets. This model can then be used to simulate network environments for network performance evaluation. We validate the simulation method through a series of experiments both in ns and over the Internet. Our experimental results show that this simulation method can represent a wide range of real network scenarios. It is easy to use, accurate and time efficient. (C) 2002 Elsevier Science B.V. All rights reserved.
In this paper, we study the use of continuous-time hidden Markov models (CT-HMMs) for network protocol and application performance evaluation. We develop an algorithm to infer the CT-HMM from a series of end-to-end de...
详细信息
In this paper, we study the use of continuous-time hidden Markov models (CT-HMMs) for network protocol and application performance evaluation. We develop an algorithm to infer the CT-HMM from a series of end-to-end delay and loss observations of probe packets. This model can then be used to simulate network environments for network performance evaluation. We validate the simulation method through a series of experiments both in ns and over the Internet. Our experimental results show that this simulation method can represent a wide range of real network scenarios. It is easy to use, accurate and time efficient. (C) 2002 Elsevier Science B.V. All rights reserved.
Presents the combination of partition-ligation (PL) strategy and expectation-maximization (em)-based algorithm in mapping single-nucleotide polymorphisms in human genomes. Application of PL-em on the lipoprotein lipas...
详细信息
Presents the combination of partition-ligation (PL) strategy and expectation-maximization (em)-based algorithm in mapping single-nucleotide polymorphisms in human genomes. Application of PL-em on the lipoprotein lipase data; Calculation for estimated haplotype frequencies; Histograms of the average error rates based on individual's phasing.
Gait analysis and classification is very important in medical diagnostics as well as athletic performance analysis. In this paper, we present a method combining spatial and temporal properties of features to classify ...
详细信息
ISBN:
(纸本)0780375084
Gait analysis and classification is very important in medical diagnostics as well as athletic performance analysis. In this paper, we present a method combining spatial and temporal properties of features to classify different gait patterns. These features are angle data coming from gait kinematics. Mixture models are used to approximate the spatial distribution of features while stationary Markov chains describe the temporal relation within the mixture models. em algorithm is implemented to compute parameters of mixture models and Markov chain models. The experiment result shows that combination between spatial properties and temporal properties gives a good way to gait analysis.
The probabilistic multi-hypothesis tracking (PMHT) algorithm is extended for application to classification. The PMHT model is reformulated as a bank of continuous-state hidden Harkov models, allowing for supervised le...
详细信息
ISBN:
(纸本)0972184414
The probabilistic multi-hypothesis tracking (PMHT) algorithm is extended for application to classification. The PMHT model is reformulated as a bank of continuous-state hidden Harkov models, allowing for supervised learning of the class-conditional probability density models, and for likelihood evaluation of multicomponent signals.
In this paper we analyse the performances of a novel approach to modelling non-linear conditionally heteroscedastic time series characterised by asymmetries in both the conditional mean and variance. This is based on ...
详细信息
暂无评论