Gravitation models, estimation methods and results
The impact of estimation methods and data frequency on the results of long memory assessment
... Finance researchers in both theoretical and empirical studies have focused on long memory (persistence) in financial asset returns. The finding of long memory in financial data would contradict the Efficient Markets ...
31
Models and Estimation Methods for Distribution of Scores for Functional Data.
... Covariance matrix rank can be selected by calculating percent of variance explained or by using an information metric, such as BIC or WAIC. B.2 FPCA Results in Simulation Study Figure B.1 through Figure B.4 show ...
131
Robust Estimation Methods And Outlier Detection In Mediation Models
... simulation results suggested that by applying our newly proposed method has improved the accuracy of the identification of high leverage point when the percentage of high leverage points is medium or ...mediation ...
25
A Comparison of Estimation Methods for Vector Autoregressive Moving-Average Models
... the results suggest that the impulse responses can be estimated more accurately by using VARMA models, provided that the model is specified ...likelihood estimation, 3SLS, seems to be superior to any ...
58
Alternative estimation methods and specification tests for moment condition models
... the results obtained in Tauchen (1986b) and also finding evidence on the tendency of the J test to reject the true hypothesis too ...simple models, with few assets, the biases of the estimators were ...
178
Fast estimation methods for time series models in state-space form
... the results obtained with two typical formulations in the state-space literature: an STSM with a low signal-to-noise ratio and an AR(2) model with observation errors, ...estimated. Results pro- vided by the ...
30
Varying coefficient models as Mixed Models : reparametrization methods and bayesian estimation
... with application of Bayesian estimates for generalized additive mod- els reparametrized by thin plate splines in a mixed model form, but no interaction term. One motivation behind this work is that p-splines are default ...
19
On Particle Methods for Parameter Estimation in State-Space Models
... parameter estimation in conditionally linear Gaus- sian models, where a part of the state is integrated out using Kalman techniques [ 15, 31 ], is proposed in [ 13 ...the methods relying on kernel or ...
24
The performance of estimation methods for generalized linear mixed models
... linear models (GLMs) are a flexible class of non-linear models for non- normally distributed response ...encompass models for discrete response data which takes one of several values rather than ...
22
Novel Methods for Estimation and Inference in Varying Coefficient Models
... coefficient models have been used to explore dynamic effect patterns in many scientific areas, such as in biomedicine, finance, and ...existing models ignore the existence of zero regions, the first chapter ...
134
Particle methods for maximum likelihood estimation in latent variable models
... obvious technique is monitoring the marginal posterior of every parameter combi- nation which is sampled and using that set of parameters associated with the largest value seen. The only obvious advantage of this method ...
16
Simulation-based Estimation Methods for Financial Time Series Models
... ML Estimation of Heston’s SV model is notoriously ...series models where asset prices do not have closed-form expressions, it is almost always the case that standard estimation methods are ...
28
Simulation-based Estimation Methods for Financial Time Series Models
... parameter estimation, MCMC provides smoothed estimates of latent variables because it augments the parameter space by including the latent ...frequentist’s methods whose inference is al- most always based ...
37
Contributions to Conditional Heteroscedastic Models: M-Estimation and Other Methods.
... p = 0 .0 1 0.0043 0.0010 0.0009 0.0096 0.0011 0.0010 0.0096 0.0011 0.0010 ft = 0 .1 0.3106 0.7253 2.3588 0.1155 1.1062 1.6271 0.0126 1.3101 1.5818 P — 0.2 -0.1028 0.8923 2.6574 -0.4087 2.0168 2.0555 -0.3579 2.2632 2.0880 ...
261
Parameter estimation of microbial models using hybrid optimization methods
... computational models (Sun et ...These models commonly contain a set of parameters that represent the physiological properties of the ...optimization methods have been proposed to estimate these ...
38
Models and Methods for Estimation and Filtering of Signal-Dependent Noise in Imaging
... this results in, respectively, sharp- ening or softening of the corresponding basis ...tensor methods developed by Feng and Milanfar [2002] and Weickert [1999], that estimate weather an image region is an ...
131
A quantitative approach to fluvial facies models: methods and example results
... facies models that are quantitative in nature and are customizable both in terms of system parameters on which they are categorized and type and scale of sedimentary units by which they are ...such models ...
96
Behind the Mind Methods, models and results in translation process research
... Another experiment using Translog – this time, for the sake of ecological validity, without the use of think aloud – is described in the paper by Brenda Malkiel, who investigates the revision process of 16 beginning ...
14
Topics in Gravitation – Numerical Simulations of Event Horizons and Parameter Estimation for LISA
... on results concerning the topology of event horizon mergers, among other ...parameter estimation of gravitational wave templates. These templates are models of the expected detector response to a ...
189
Dynamic probit models for panel data: A comparison of three methods of estimation
... Motivation 3 Methods Monte Carlo Study Simulation results Conclusions Orme (1996) method.. Orme suggests a two-step bias corrected procedure that is locally valid when ρ approximates to [r] ...
21