搜索结果: 1-15 共查到“统计学其他学科 Modeling”相关记录17条 . 查询时间(0.2 秒)
ARMA Time-Series Modeling with Graphical Models
ARMA Time-Series Modeling Graphical Models
2012/9/19
We express the classic ARMA time-series model as a directed graphical model. In doing so, we find that the deterministic re-lationships in the model make it effectively impossible to use the EM algori...
Modeling Waveform Shapes with Random Eects Segmental Hidden Markov Models
Modeling Waveform Shapes Random Eects Segmental Hidden Markov Models
2012/9/19
In this paper we describe a general probabilis-tic framework for modeling waveforms such as heartbeats from ECGdata. The model is based on segmental hidden Markov mod-els(as usedin speechrecognition) ...
Modeling Waveform Shapes with Random Eects Segmental Hidden Markov Models
Modeling Waveform Shapes Random Eects Segmental Hidden Markov Models
2012/9/19
In this paper we describe a general probabilis-tic framework for modeling waveforms such as heartbeats from ECGdata. The model is based on segmental hidden Markov mod-els(as usedin speechrecognition) ...
A non-parametric mixture model for topic modeling over time
non-parametric mixture model topic modeling over time
2012/9/17
A single, stationary topic model such as la-tent Dirichlet allocation is inappropriate for modeling corpora that span long time peri-ods, as the popularity of topics is likely to change over time. A n...
A Unified Approach for Modeling and Recognition of Individual Actions and Group Activities
A Unified Approach for Modeling Recognition of Individual Actions Group Activities
2012/9/18
Recognizing group activities is challenging due to the di-culties in isolating individual entities, nding the respective roles played by the individuals and representing the complex interactions amo...
Inverse Modeling of Dynamical Systems: Multi-Dimensional Extensions of a Stochastic Switching Problem
Inverse Modeling of Dynamical Systems Multi-Dimensional Extensions Stochastic Switching Problem
2012/9/18
The Buridan's ass paradox is characterized by perpetual indecision between two states, which are never attained. When this problem is formulated as a dynamical
system, indecision is modeled by a disc...
Rejoinder to "Statistical Modeling of Spatial Extremes"
Rejoinder "Statistical Modeling of Spatial Extremes"
2012/9/17
We are grateful to the discussants for their posi-tive and interesting comments. In an area moving so rapidly it is to be expected that our review overlooks
some work, and all the contributions helpf...
Discussion of "Statistical Modeling of Spatial Extremes" by A. C. Davison, S. A. Padoan and M. Ribatet
Discussion "Statistical Modeling of Spatial Extremes" A. C. Davison, S. A. Padoan A. C. Davison, S. A. Padoan and M. Ribatet M. Ribatet
2012/9/17
We congratulate the authors for producing such a helpful and comprehensive overview paper of a ra-pidly developing and important area. The starting point for inference in spatial extreme value prob-le...
Discussion of "Statistical Modeling of Spatial Extremes" by A. C. Davison, S. A. Padoan and M. Ribatet
Discussion "Statistical Modeling of Spatial Extremes" A. C. Davison, S. A. Padoan M. Ribatet
2012/9/17
The review paper on spatial extremes by Davison,Padoan and Ribatet is a most welcome contribu-tion. The authors cover quite a lot of ground, mak-ing connections between different approaches while high...
Discussion of "Statistical Modeling of Spatial Extremes" by A. C. Davison, S. A. Padoan and M. Ribatet
Discussio "Statistical Modeling of Spatial Extremes" A. C. Davison, S. A. Padoan M. Ribatet
2012/9/17
We congratulate the authors for their overview paper discussing modeling techniques for spatial ex-tremes. There is great interest in spatial extreme
data in the atmospheric science community, as the...
Statistical Modeling of Spatial Extremes
Annual maximum analysis Bayesian hierar-chical model Brown–Resnick process composite likelihood copula en-vironmental data analysis Gaussian process generalizedextreme-value distribution geostatistics latent variable max-stable process statistics of extremes
2012/9/17
The areal modeling of the extremes of a natural process such as rainfall or temperature is important in environmental statistics; for example, understanding extreme areal rainfall is crucial in flood ...
Nested hidden Markov chains for modeling dynamic unobserved heterogeneity in multilevel longitudinal data
composite likelihood EM algorithm latent Markov model pairwise likelihood
2012/9/17
In the context of multilevel longitudinal data, where sample units are collected in clusters, an important aspect that should be accounted for is the unobserved heterogeneity between sample units and ...
Dealing with nonresponse in survey sampling: a latent modeling approach
unit nonresponse item nonresponse latent trait models response propensity non-ignorable nonresponse
2012/9/19
Nonresponse is present in almost all surveys and can severely bias estimates. It is usually distinguished between unit and item nonresponse: in the former, we completely fail to have information from ...
Flexible Mixture Modeling with the Polynomial Gaussian Cluster-Weighted Model
Mixture of distributions Mixture of regressions Polynomial regression Model-based clustering Model-based classification Cluster-weighted models.
2012/9/18
In the mixture modeling frame, this paper presents the polynomial Gaussian cluster-weighted model (CWM). It extends the linear Gaussian CWM, for bivariate data, in a twofold way. Firstly, it allows fo...
Sparse Vector Autoregressive Modeling
vector autoregressive (VAR) model sparsity partial spectral coherence (PSC) model selection.
2012/9/18
The vector autoregressive (VAR) model has been widely used for modeling temporal de-pendence in a multivariate time series. For large (and even moderate) dimensions, the number of AR coefficients can ...