| 1. |
- Ahmed, S. Ejaz, et al.
(författare)
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Estimation of Several Intraclass Correlation Coefficients
- 2015
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Ingår i: Communications in statistics. Simulation and computation. - : Informa UK Limited. - 0361-0918 .- 1532-4141. ; 44:9, s. 2315-2328
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Tidskriftsartikel (refereegranskat)abstract
- An intraclass correlation coefficient observed in several populations is estimated. The basis is a variance-stabilizing transformation. It is shown that the intraclass correlation coefficient from any elliptical distribution should be transformed in the same way. Four estimators are compared. An estimator where the components in a vector consisting of the transformed intraclass correlation coefficients are estimated separately, an estimator based on a weighted average of these components, a pretest estimator where the equality of the components is tested and then the outcome of the test is used in the estimation procedure, and a James-Stein estimator which shrinks toward the mean.
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| 2. |
- Holgersson, Thomas, et al.
(författare)
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Testing for Panel Unit Roots under General Cross-sectional Dependence
- 2016
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Ingår i: Communications in Statistics-Simulation and Computation. - : Informa UK Limited. - 0361-0918 .- 1532-4141. ; 45:5, s. 1785-1801
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Tidskriftsartikel (refereegranskat)abstract
- In this article, we generalize four tests of multivariate linear hypothesis to panel data unit root testing. The test statistics are invariant to certain linear transformations of data and therefore simulated critical values may conveniently be used. It is demonstrated that all four tests remains well behaved in cases of where there are heterogeneous alternatives and cross-correlations between marginal variables. A Monte Carlo simulation is included to compare and contrast the tests with two well-established ones.
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| 3. |
- Hossain, Md Mobarak, et al.
(författare)
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A novel weighted likelihood estimation with empirical Bayes flavor
- 2018
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Ingår i: Communications in Statistics: Simulation and Computation. - : Informa UK Limited. - 0361-0918 .- 1532-4141. ; 47:2, s. 392-412
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Tidskriftsartikel (refereegranskat)abstract
- We propose a novel approach to estimation, where a set of estimators of a parameter is combined into a weighted average to produce the final estimator. The weights are chosen to be proportional to the likelihood evaluated at the estimators. We investigate the method for a set of estimators obtained by using the maximum likelihood principle applied to each individual observation. The method can be viewed as a Bayesian approach with a data-driven prior distribution. We provide several examples illustrating the new method and argue for its consistency, asymptotic normality, and efficiency. We also conduct simulation studies to assess the performance of the estimators. This straightforward methodology produces consistent estimators comparable with those obtained by the maximum likelihood method. The method also approximates the distribution of the estimator through the “posterior” distribution.
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| 4. |
- Kibria, B. M. Golam, et al.
(författare)
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A simulation study of some biasing parameters for the ridge type estimation of Poisson regression
- 2015
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Ingår i: Communications in statistics. Simulation and computation. - : Taylor & Francis. - 0361-0918 .- 1532-4141. ; 44:4, s. 943-957
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Tidskriftsartikel (refereegranskat)abstract
- This paper proposes several estimators for estimating the ridge parameter k based for Poisson ridge regression (RR) model. These estimators have been evaluated by means of Monte Carlo simulations. As performance criteria, we have calculated the mean squared error (MSE), the mean value and the standard deviation of k. The first criterion is commonly used, while the other two have never been used when analyzing Poisson RR. However, these performance criterion are very informative because, if several estimators have an equal estimated MSE then those with low average value and standard deviation of k should be preferred. Based on the simulated results we may recommend some biasing parameters which may be useful for the practitioners in the field of health, social and physical sciences.
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| 5. |
- Picchini, Umberto
(författare)
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Likelihood-free stochastic approximation EM for inference in complex models
- 2019
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Ingår i: Communications in Statistics: Simulation and Computation. - : Informa UK Limited. - 0361-0918 .- 1532-4141. ; 48:3, s. 861-881
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Tidskriftsartikel (refereegranskat)abstract
- A maximum likelihood methodology for the parameters of models with an intractable likelihood is introduced. We produce a likelihood-free version of the stochastic approximation expectation-maximization (SAEM) algorithm to maximize the likelihood function of model parameters. While SAEM is best suited for models having a tractable "complete likelihood" function, its application to moderately complex models is a difficult or even impossible task. We show how to construct a likelihood-free version of SAEM by using the "synthetic likelihood" paradigm. Our method is completely plug-and-play, requires almost no tuning and can be applied to both static and dynamic models. Four simulation studies illustrate the method, including a stochastic differential equation model, a stochastic Lotka-Volterra model and data from g-and-k distributions. MATLAB code is available as supplementary material.
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| 6. |
- Pingel, Ronnie, et al.
(författare)
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Correlation and Efficiency of Propensity Score-based Estimators for Average Causal Effects
- 2017
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Ingår i: Communications in statistics. Simulation and computation. - : Informa UK Limited. - 0361-0918 .- 1532-4141. ; 46:5, s. 3458-3478
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Tidskriftsartikel (refereegranskat)abstract
- Propensity score based-estimators are commonly used to estimate causal effects in evaluationresearch. To reduce bias in observational studies researchers might be tempted to include many, perhaps correlated, covariates when estimating the propensity score model. Taking into account that the propensity score is estimated, this study investigates how the efficiency of matching, inverse probability weighting and doubly robust estimators change under the case of correlated covariates. Propositions regarding the large sample variances under certain assumptions on the data generating process are given. The propositions are supplemented by several numerical large sample and finite sample results from a wide range of models. The results show that the covariate correlations may increase or decrease the variances of the estimators. There are several factors that influence how correlation affects the variance of the estimators, including the choice of estimator, the strength of the confounding towards outcome and treatment, and whether a constant or non-constant causal effect is present.
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| 7. |
- Riazoshams, Hossein, et al.
(författare)
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The Performance of a Robust Multistage Estimator in Nonlinear Regression with Heteroscedastic Errors
- 2016
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Ingår i: Communications in statistics. Simulation and computation. - : Informa UK Limited. - 0361-0918 .- 1532-4141. ; 45:9, s. 3394-3415
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Tidskriftsartikel (refereegranskat)abstract
- In this article, a robust multistage parameter estimator is proposed for nonlinear regression with heteroscedastic variance, where the residual variances are considered as a general parametric function of predictors. The motivation is based on considering the chi-square distribution for the calculated sample variance of the data. It is shown that outliers that are influential in nonlinear regression parameter estimates are not necessarily influential in calculating the sample variance. This matter persuades us, not only to robustify the estimate of the parameters of the models for both the regression function and the variance, but also to replace the sample variance of the data by a robust scale estimate.
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| 8. |
- Shukur, Ghazi, et al.
(författare)
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A new nonlinear asymmetric cointegration approach using error correction models
- 2017
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Ingår i: Communications in statistics. Simulation and computation. - : Taylor & Francis. - 0361-0918 .- 1532-4141. ; 46:2, s. 1661-1668
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Tidskriftsartikel (refereegranskat)abstract
- In this article, two new powerful tests for cointegration are proposed. The general idea is based on an intuitively appealing extension of the traditional, rather restrictive cointegration concept. In this article, we allow for a nonlinear, but most importantly a different, asymmetric convergence process to account for negative and positive changes in our cointegration approach. Using Monte Carlo simulations we verify, that the estimated size of the first test depends on the unknown value of a signal-to-noise ratio q. However, our second test—which is based on the original ideas of Kanioura and Turner—is more successful and robust in the sense that it works in all of the different evaluated situations. Furthermore it is shown to be more powerful than the traditional residual based Enders and Siklos method. The new optimal test is also applied in an empirical example in order to test for potential nonlinear asymmetric price transmission effects on the Swedish power market. We find that there is a higher propensity for power retailers to rapidly and systematically increase their retail electricity prices subsequent to increases in Nordpool's wholesale prices, than there is for them to reduce their prices subsequent to a drop in wholesale spot prices.
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| 9. |
- Shukur, Ghazi, et al.
(författare)
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Comparison of the effectiveness of forecasts obtained by means of selected probability functions with respect to forecast error distributions
- 2017
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Ingår i: Communications in statistics. Simulation and computation. - : Taylor & Francis. - 0361-0918 .- 1532-4141. ; 46:5, s. 3667-3679
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Tidskriftsartikel (refereegranskat)abstract
- The Forecasting of sales in a company is one of the crucial challenges that must be faced. Nowadays, there is a large spectrum of methods that enable making reliable forecasts. However, sometimes the nature of time series excludes many well-known and widely used forecasting methods (e.g. econometric models). Therefore, the authors decided to forecast on the basis of a seasonally adjusted median of selected probability distributions. The obtained forecasts were verified by means of distributions of the Theil U2 coefficient and unbiasedness coefficient.
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| 10. |
- Sjölander, Pär, et al.
(författare)
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Testing for panel cointegration in an error-correction framework with an application to the Fisher hypothesis
- 2017
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Ingår i: Communications in statistics. Simulation and computation. - : Taylor & Francis. - 0361-0918 .- 1532-4141. ; 46:3, s. 1735-1745
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Tidskriftsartikel (refereegranskat)abstract
- In this article, three innovative panel error-correction model (PECM) tests are proposed. These tests are based on the multivariate versions of the Wald (W), likelihood ratio (LR), and Lagrange multiplier (LM) tests. Using Monte Carlo simulations, the size and power of the tests are investigated when the error terms exhibit both cross-sectional dependence and independence. We find that the LM test is the best option when the error terms follow independent white-noise processes. However, in the more empirically relevant case of cross-sectional dependence, we conclude that the W test is the optimal choice. In contrast to previous studies, our method is general and does not rely on the strict assumption that a common factor causes the cross-sectional dependency. In an empirical application, our method is also demonstrated in terms of the Fisher effect—a hypothesis about the existence of which there is still no clear consensus. Based on our sample of the five Nordic countries we utilize our powerful test and discover evidence which, in contrast to most previous research, confirms the Fisher effect.
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