搜索结果: 16-30 共查到“管理学 modeling”相关记录82条 . 查询时间(0.375 秒)
Bayesian Multi-Dipole Modeling of Single MEG Topographies by Adaptive Sequential Monte Carlo Samplers
Magnetoencephalography inverse problem Multi-object estimation Multi-dipole models Adaptive Sequential Monte Carlo samplers
2013/6/14
We describe a novel Bayesian approach to the estimation of neural currents from a single distribution of magnetic field, measured by magnetoencephalography. We model neural currents as an unknown numb...
Modeling Information Propagation with Survival Theory
Modeling Information Propagation Survival Theory
2013/6/14
Networks provide a skeleton for the spread of contagions, like, information, ideas, behaviors and diseases. Many times networks over which contagions diffuse are unobserved and need to be inferred. He...
Modeling Temporal Activity Patterns in Dynamic Social Networks
Activity Profile Modeling Twitter Data-Fitting Explanation Prediction Hidden Markov Model Coupled Hidden Markov Model Social Network In uence User Clustering
2013/6/14
The focus of this work is on developing probabilistic models for user activity in social networks by incorporating the social network influence as perceived by the user. For this, we propose a coupled...
Joint Topic Modeling and Factor Analysis of Textual Information and Graded Response Data
Factor analysis topic model personalized learning machine learning block coordinate descent
2013/6/14
Modern machine learning methods are critical to the development of large-scale personalized learning systems that cater directly to the needs of individual learners. The recently developed SPARse Fact...
Bayesian Modeling and MCMC Computation in Linear Logistic Regression for Presence-only Data
Bayesian modeling case-control design data augmentation logistic regres-sion Markov Chain Monte Carlo population prevalence presence-only data simulation
2013/6/13
Presence-only data are referred to situations in which, given a censoring mechanism, a binary response can be observed only with respect to on outcome, usually called \textit{presence}. In this work w...
Robots rely on sensors to provide them with information about their surroundings. However, high-quality sensors can be extremely expensive and cost-prohibitive. Thus many robotic systems must make due...
A QUALITY ANALYSIS AND UNCERTAINTY MODELING APPROACH FOR CROWD-SOURCING LOCATION CHECK-IN DATA
Crowd-sourcing Location check-in Quality analysis Spatial registration Uncertainty Error distribution
2014/4/24
The location check-in data, developing along with social network, are considered as user-generated crowd-sourcing geospatial data.
With massive data volume, abundance in contained information, and h...
Two General Methods for Population Pharmacokinetic Modeling: Non-Parametric Adaptive Grid and Non-Parametric Bayesian
Population pharmacokinetic modeling non-parametric maximum likelihood Bayesian Stick-breaking Pmetrics RJags
2013/5/2
Population pharmacokinetic (PK) modeling methods can be statistically classified as either parametric or nonparametric (NP). Each classification can be divided into maximum likelihood (ML) or Bayesian...
Modeling US house prices by spatial dynamic structural equation models
house prices Bayesian inference dynamic factor models spatio-temporal models cointegration lattice data
2013/4/27
This article proposes a spatial dynamic structural equation model for the analysis of housing prices at the State level in the USA. The study contributes to the existing literature by extending the us...
Quantile correlations and quantile autoregressive modeling
Autocorrelation function Box-Jenkins method Quantile correlation Quantile partial correlation Quantile autoregressive model
2012/11/23
In this paper, we propose two important measures, quantile correlation (QCOR) and quantile partial correlation (QPCOR). We then apply them to quantile autoregressive (QAR) models, and introduce two va...
Modeling left-truncated and right-censored survival data with longitudinal covariates
Likelihood approach semiparametric efficiency biased sample EM algorithm Monte Carlo integration
2012/11/23
There is a surge in medical follow-up studies that include longitudinal covariates in the modeling of survival data. So far, the focus has been largely on right-censored survival data. We consider sur...
Negative Binomial Process Count and Mixture Modeling
Negative Binomial Process Count and Mixture Modeling
2012/11/22
The seemingly disjoint problems of count and mixture modeling are united under the negative binomial (NB) process. We reveal relationships between the Poisson, multinomial, gamma and Dirichlet distrib...
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) ...