Search Results - subject:"ML estimation"

Predicting volatility based on interval regression models

Qu, Hui; He, Mengying - In: Journal of risk and financial management : JRFM 15 (2022) 12, pp. 1-21

Considering the inferior volatility tracking capability of the point-data-based models, we propose using the more informative price interval data and building interval regression models for volatility forecasting. To characterize the heterogeneity of the market and the nonlinearity of...

Persistent link: https://www.econbiz.de/10014284403

Parameter estimation of exponentiated exponential distribution under selective ranked set sampling

Hassan, Amal S.; Elshaarawy, Rasha S.; Nagy, Heba F. - In: Statistics in transition : an international journal of … 23 (2022) 4, pp. 37-58

Partial ranked set sampling (PRSS) is a cost-effective sampling method. It is a combination of simple random sample (SRS) and ranked set sampling (RSS) designs. The PRSS method allows flexibility for the experimenter in selecting the sample when it is either difficult to rank the units within...

Persistent link: https://www.econbiz.de/10014287878

Zero-modified Poisson-Modification of Quasi Lindley distribution and its application

Tharshan, Ramajeyam; Wijekoon, Pushpakanthie - In: Statistics in transition : an international journal of … 23 (2022) 4, pp. 113-128

asymptotic theory of the ML estimation method and to show the superiority of the ML method over the method of moments estimation … dispersion, and quantile function are presented. Furthermore, some of its special cases are discussed. The maximum likelihood (ML …) estimation method is used for the unknown parameter estimation. A simulation study is conducted in order to evaluate the …

Persistent link: https://www.econbiz.de/10014287906

Testing conditional moment restriction models using empirical likelihood

Berger, Yves G. - In: The econometrics journal 25 (2022) 2, pp. 384-403

Persistent link: https://www.econbiz.de/10013253841

The generalized spatial random effects model in R

Millo, Giovanni - 2022

Persistent link: https://www.econbiz.de/10013259918

Novel techniques for Bayesian inference in univariate and multivariate stochastic volatility models

Tsionas, Efthymios G. - 2022

Persistent link: https://www.econbiz.de/10013193282

Trend-cycle decompositions of real GDP revisited : classical and Bayesian perspectives on an unsolved puzzle

Kim, Chang-jin; Kim, Jaeho - In: Macroeconomic dynamics 26 (2022) 2, pp. 394-418

Persistent link: https://www.econbiz.de/10013166386

State-dependent Hawkes processes and their application to limit order book modelling

Morariu-Patrichi, Maxime; Pakkanen, Mikko S. - In: Quantitative finance 22 (2022) 3, pp. 563-583

Persistent link: https://www.econbiz.de/10013167781

Piecewise-Linear Approximations and Filtering for DSGE Models with Occasionally Binding Constraints

Aruoba, S. Borağan; Cuba-Borda, Pablo; Higa-Flores, Kenji - 2022

We develop an algorithm to construct approximate decision rules that are piecewise-linear and continuous for DSGE models with an occasionally binding constraint. The functional form of the decision rules allows us to derive a conditionally optimal particle filter (COPF) for the evaluation of the...

Persistent link: https://www.econbiz.de/10014091400

Finite sample comparison of alternative estimators for fractional Gaussian noise

Shi, Shuping; Yu, Jun; Zhang, Chen - 2022

Persistent link: https://www.econbiz.de/10013542219