[PDF] Top 20 Maximum likelihood estimation for directional conditionally autoregressive models
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Maximum likelihood estimation for directional conditionally autoregressive models
... From the results based on the ML estimates of CAR model, we observe that for all the cases there are no significant biases at 5% level. The ESE of ρ is a good approximation to finite sample variance when the spatial ... See full document
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Modified Maximum Likelihood Estimation in Autoregressive Processes with Generalized Exponential Innovations
... first-order autoregressive er- rors belonging to the class of heavy-tailed ...regression models with independent error, since the er- ror distribution covers both correlated innovations following a ... See full document
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Change Point Estimation of the Stationary State in Auto Regressive Moving Average Models, Using Maximum Likelihood Estimation and Singular Value Decomposition-based Filtering
... the autoregressive (AR(1)) model of the first order and the model of the autoregressive moving average (ARMA(1,1)), Safaeipour and Niaki [1] modelled a multistep process of an individual feature monitored ... See full document
11
Maximum likelihood estimation of higher-order integer-valued autoregressive processes
... variable models are apparently inappropriate in that they would in- variably produce non-integer forecast ...series models has to be entertained to explicitly account for the ...observation-driven ... See full document
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Maximum likelihood estimation of time series models: the Kalman filter and beyond
... space models and provides the state space representation of some commonly applied linear processes, such as univariate and multivariate autoregressive moving average processes (ARMA) and dynamic factor ... See full document
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Maximum likelihood estimation in possibly misspecified dynamic models with time inhomogeneous Markov Regimes
... in models with time-inhomogeneous Markov regimes involves the use of an incomplete approximation to the likelihood function which ignores the joint dependence of the observation variable and of the ... See full document
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Computational approaches for maximum likelihood estimation for nonlinearmixed models.
... other models f , magnitudes of variation, and other ...mixed models suggest that estima- tion of conditionally linear parameters in the present context may be less aected by nonnormality of random ... See full document
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Generalized quasi maximum likelihood inference for periodic conditionally heteroskedastic models
... the AutoRegressive Conditionally Heteroskedastic (ARCH ) model by Engle (1982) and its leading GARCH generalization by Bollerslev (1986), conditional volatility models have continued to capture the ... See full document
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Likelihood Inference for Generalized Integer Autoregressive Time Series Models
... original estimation method in Du and Li (1991) is Yule-Walker or method of ...approximate likelihood inference method based on the saddlepoint approximation is used in Pedeli et ...of maximum ... See full document
13
Generalized Conditionally Autoregressive Models
... the likelihood-based estimations. When the exact likelihood is unavailable, modified methods are used (for example, pseudo-likelihood estimation (Gong and Samaniego, ...parameter ... See full document
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Normal mixture quasi maximum likelihood estimation for non-stationary TGARCH(1,1) models
... generalized autoregressive conditional heteroscedastic (GARCH) models have been proved particularly valuable in mod- elling time varying ...GARCH models is based on least-squares estimation ... See full document
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Maximum likelihood parameter estimation for latent variable models using sequential Monte Carlo
... We present a sequential Monte Carlo (SMC) method for maximum likelihood (ML) parameter estimation in latent variable models. Stan- dard methods rely on gradient algorithms such as the ... See full document
5
Estimation of the Reliability Measures of a Three component System with Human Errors and Common Cause Failures
... Therefore, the M L estimators are generally hard to beat consistently, even in small samples and our simulation results showed a strong preference for the M L estimation method for situations arising in practical ... See full document
7
Some aspects of estimation for vector time series models
... of models that have identical covariance matrix ...of models associated with ...ARMA models has been extensively studied see, for example, Hannan (1969, 1979), Akaike (1976) and the references ... See full document
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Maximum Likelihood Estimation of Feature Based Distributions
... Second, models can be defined where multiple features are permitted to ...or models where only certain features are permitted to interact but not others (perhaps because they belong to the same node in a ... See full document
10
THE APPLICATION OF THE "METHOD OF MAXIMUM LIKELIHOOD" TO THE ESTIMATION OF LINKAGE
... F1cmv3.-A factor linked to one of two duplicate factors: Amount of information concerning linkage supplied per plant by a backcross to a triple recessive, and by an Fz, using ([r] ... See full document
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Maximum Entropy and Maximum Likelihood Estimation for the Three Parameter Kappa Distribution
... Samples are drawn from positively skew or heavy-tailed distributions, located on the right far from the mean. Sta- tistically, such values are considered to be outliers and consequently strongly influence the sample ... See full document
5
The use of heuristic optimization algorithms to facilitate maximum simulated likelihood estimation of random parameter logit models
... Another practically attractive feature of the DE-assisted solutions is clearer indicative evi- dence on which configurations are likely to work well. Tables 3 and 4 report the top 10 logL-values found with the aid of each ... See full document
17
A simple approach to maximum intractable likelihood estimation
... the likelihood function, even up to a normalising constant, is impossible or computationally ...Composite Likelihood methods (Cox and Reid, 2004), for approximating the likelihood function, and ... See full document
24
On the Approximate Maximum Likelihood Estimation for Diffusion Processes
... We report results from simulation studies which are designed to confirm the theoretical findings on the AMLE as reported in the earlier sections. To allow verification with the full MLE, we considered the Vasicek and CIR ... See full document
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