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[PDF] Top 20 Maximum likelihood estimation for stochastic processes - a martingale approach

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Maximum likelihood estimation for stochastic processes - a martingale approach

Maximum likelihood estimation for stochastic processes - a martingale approach

... for processes which have continuous sample paths, it may be a very good approximation to act as if the process was being observed ...time processes are limits of related discrete time processes so ... See full document

228

Unified quasi maximum likelihood estimation theory for stable and unstable Markov bilinear processes

Unified quasi maximum likelihood estimation theory for stable and unstable Markov bilinear processes

... uni…ed estimation theory, strict stationarity testing for the SM BL equation is ...nonstationary stochastic unit root case, the QM LE is still consistent when (1:2) is appropriately ... See full document

31

Maximum likelihood estimation for stochastic Lotka–Volterra model with jumps

Maximum likelihood estimation for stochastic Lotka–Volterra model with jumps

... popular approach to model population dynamics perturbed by random environment, has recently been studied by many authors both from a mathematical perspective and in the context of real biologi- cal ... See full document

22

Modelling stochastic volatility with leverage and jumps: a
simulated maximum likelihood approach via particle filtering

Modelling stochastic volatility with leverage and jumps: a simulated maximum likelihood approach via particle filtering

... the stochastic volatility literature was made by Harvey and Shephard ...Quasi Maximum Likelihood (QML) technique used in parameter estimation in standard SV models (see Harvey et ...QML ... See full document

29

A simple approach to maximum intractable likelihood estimation

A simple approach to maximum intractable likelihood estimation

... the likelihood function, even up to a normalising constant, is impossible or computationally ...and stochastic dynamical systems pro- vide numerous examples of this (see ...Composite Likelihood ... See full document

24

Estimation of stochastic volatility models via Monte Carlo maximum likelihood

Estimation of stochastic volatility models via Monte Carlo maximum likelihood

... Bayesian approach to the estimation of SV models using a Monte Carlo Markov chain (MCMC) technique was developed by Jacquier et ...MM estimation techniques across a wide range of parameter ... See full document

31

Maximum likelihood estimation of a stochastic frontier model with residual covariance

Maximum likelihood estimation of a stochastic frontier model with residual covariance

... the maximum likelihood approach for estimating a stochastic production frontier ...the maximum likelihood estimation procedure suggested in Cliff and Ord (1973) and ... See full document

12

Variable bandwidth local maximum likelihood type estimation for diffusion processes

Variable bandwidth local maximum likelihood type estimation for diffusion processes

... robust approach is applied to estimate drift function and diffusion function of diffusion processes with discrete-time ...and maximum likelihood type estimation technique, so the ... See full document

21

Simulated maximum likelihood for general stochastic volatility models: a change of variable approach

Simulated maximum likelihood for general stochastic volatility models: a change of variable approach

... Maximum likelihood has proved to be a valuable tool for fitting the log-normal stochastic volatility model to financial returns time ...general stochastic volatility models into a form ... See full document

24

Estimation of Technical and Allocative Inefficiencies in a Cost System: An Exact Maximum Likelihood Approach

Estimation of Technical and Allocative Inefficiencies in a Cost System: An Exact Maximum Likelihood Approach

... the stochastic frontier literature there are two approaches to estimate a system and obtain measures of increased cost due to technical and allocative efficiencies under the behavioral assumption of cost ...system ... See full document

32

Parameter estimation for the stochastic SIS epidemic model

Parameter estimation for the stochastic SIS epidemic model

... parameter estimation in stochastic differential equations (SDEs) is a non-trivial problem [2, ...to estimation im- possible to ...parameter estimation methods for continuous time ...between ... See full document

26

Maximum likelihood estimation for multiscale Ornstein Uhlenbeck processes

Maximum likelihood estimation for multiscale Ornstein Uhlenbeck processes

... A necessary step in statistical modelling is to fit the chosen model to the data by in- ferring the value of the unknown parameters. In the case of stochastic differential equations (SDE), this is a well studied ... See full document

28

On the Approximate Maximum Likelihood Estimation for Diffusion Processes

On the Approximate Maximum Likelihood Estimation for Diffusion Processes

... multivariate processes in A¨ıt-Sahalia ...approximate likelihood functions, which are maximized to obtain the approximate maximum likelihood estimators ...approximate likelihood ... See full document

39

Method of Maximum Likelihood Estimation of Optimal Number of Factors: An Information Criteria Approach

Method of Maximum Likelihood Estimation of Optimal Number of Factors: An Information Criteria Approach

... complex and diverse relationships that exist among a set of observed variables by uncovering common dimensions or factors that link together the seemingly unrelated variables and consequently provides insight into the ... See full document

11

Maximum Likelihood Estimation of Feature Based Distributions

Maximum Likelihood Estimation of Feature Based Distributions

... Finally, we compare this proposal with Hayes and Wilson (2008). Essentially, the model here represents a “bottom-up” approach whereas theirs is “top-down.” “Top-down” models, which con- sider every set of features ... See full document

10

Maximum likelihood estimation of variance components

Maximum likelihood estimation of variance components

... the estimation of variance components has been a rich source of research problems over the last ...which estimation method is to be preferred in a particular ... See full document

76

Lists in a Lighthouse

Lists in a Lighthouse

... The command firthglm can be applied to any generalized linear model and canonical link supported by Stata's glm command using penalized log-likelihood. We illustrate another model using data provided by Dr. José ... See full document

101

Maximum likelihood approach to DoA estimation using lens antenna array

Maximum likelihood approach to DoA estimation using lens antenna array

... selection approach has received much attention [12, ...power approach can be tailored to choose an antennas which have the maximum power and its two nearby ... See full document

7

Maximum likelihood estimation of population parameters.

Maximum likelihood estimation of population parameters.

... Under the assumptions that sequences are infinitely long and that the scaled coalescent times can be estimated without error, FELSENSTEIN (1992) showed that the improvement [r] ... See full document

10

Estimation in Interacting Diffusions: Continuous and Discrete Sampling

Estimation in Interacting Diffusions: Continuous and Discrete Sampling

... approximate maximum likelihood esti- mator of the drift coefficient of an interacting particles of diffusions are ...approximate maximum likelihood estimator, dis- crete observations are taken ... See full document

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