Latent-State Model and Estimation
On nonparametric estimation of the latent distribution for ordinal data
... the latent variable into intervals correspond- ing to the observed levels of the ordinal ...This latent distribution is of interest to researchers for purposes of descriptive statistics and sta- tistical ...
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Latent state estimation in a class of nonlinear systems
... An application of the sigma point generation, introduced in chapter 4, in financial portfolio opti- mization is presented in chapter 6. One of the traditional approaches for decision making under uncertainty and risk is ...
123
Nonparametric spectral-based estimation of latent structures
... probit model s t = 1{s t−1 ≥ ε t }, ε t ∼ N (0, 1), and subsequently drew y t from a left-skewed beta distribution on [−1, 1] when s t = 0 and from a right-skewed beta distribution when s t = ...positive ...
26
Maximum Likelihood Estimation of Latent Affine Processes
... the state variable can be accommodated, whereas simulation methods can have difficulty with rare ...volatility model examined inter alia by Harvey, Ruiz, and Shephard (1994) and Jacquier, Polson, and Rossi ...
38
Particle Smoothing and Latent Process Estimation in Neuroscience
... estimate model parameters, one needs knowledge of the posterior distributions over these processes given the ...of state-space models in the context of neuroscience and ...The estimation of the ...
205
Maximum Reconstruction Estimation for Generative Latent-Variable Models
... Comparison with MLE Table 1 shows the comparison of MLE and MRE. With the increase of the number of hidden states, the expressiveness of HMMs generally im- proves accordingly. We find that MRE outperforms MLE for ...
7
Simulated Maximum Likelihood Estimation for Latent Diffusion Models
... multiple latent state ...the model speci c µ t , Σ t and Q t ...the latent process are important parameters for whether this would be ...
30
A Bayesian approach to estimation of dynamic models with small and large number of heterogeneous players and latent serially correlated state
... 4 Evaluating the Likelihood In this section we derive an unbiased particle filter estimate of the likelihood for a Markov process with partially observed state and endogenous feedback that is general enough to ...
40
Model-based analysis of latent factors
... in model-based analyses of la- tent factors, and this justifies briefly outlining their essen- tial features and potential ...include estimation of assignments of maximum likelihood or pos- terior ...the ...
10
Flexible characterization of animal movement pattern using net squared displacement and a latent state model
... Methods Model formulation and estimation Net squared displacement is obtained from a series of locations by calculating the square of the Euclidean dis- tance between a given location and the putative ...
12
Estimation of the number of incidence in the epidemic dynamics model with latent period
... dynamic model of infectious diseases, the use of traditional methods to estimate the number of incidence, there is often a theoretical analysis of high complexity, immediacy and ...dynamic model of the ...
6
Bayesian Estimation of Latent Class Model for Survey Data Subject to Item Nonresponse
... the latent variable and its two classes, this indicates that the probability of having high access to knowledge sources is higher for older, richer males with higher levels of education for those living in rural ...
16
Robust Latent Ability Estimation Based on Item Response Information and Model Fit
... One exception is the analyses based on the person response function (PRF; Trabin & Weiss, 1983). The PRF gives the probability of a correct answer for an individual with a fixed ability as a function of item ...
108
A model based approach for state estimation for networks
... process model. It is a higher order LWR model, which is more suitable than a first order model because of the more correlations between links that can be captured and lead to more opportunities for ...
86
Optimal state estimation of a navigation model system
... error state of the latitude, longitude and height with their corresponding 3-sigma bounds, (these bounds set out the interval in which all the estimated error states should be with the probability ...
109
GMM Estimation of the Number of Latent Factors
... GMM estimation results could change depending on the partition we ...The model selection criterion method is less sensitive to the partitions than the sequential testing method ...
42
Estimation of Growth Modulation Index Using Latent Variable and Accelerated Failure Time Model
... (RPSFT) model and Accelerated Failure Time (AFT) ...using latent variable approach and AFT model exhibited smaller bias and MSE than the previous estimates based on the Kaplan-Meier survival ...
6
A canonical space-time state space model: state and parameter estimation
... joint state and parameter estimation problem for the general, linear state-space ...spatio–temporal model outlined earlier, the construction of the likelihood for the EM algorithm’s M-step ...
10
Insights on the role of accurate state estimation in coupled model parameter estimation by a conceptual climate model study
... coupled model PE is applied to a CGCM with the real observing sys- ...of state estimation impacts on the cou- pled model parameter estimation is an interesting and chal- lenging ...
15
Hydrologic Data Assimilation: State Estimation and Model Calibration
... (snow model) and SACramento Soil Moisture Accounting (SAC-SMA) ...Emission Model for Layered Snowpack model to assimilate microwave radiance ...SAC-SMA model. Several scenarios on state ...
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