A useful extension of the generalized linear model involves the addition of random effects andlor correlated errors. A pseudo-likelihood estimation procedure is developed to fit this class of mixed models based on an approximate marginal model for the mean response. The procedure is implemented via iterated fitting of a weighted Gaussian linear mixed model to…
Journal of Statistical Computation and Simulation Template
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About the Journal of Statistical Computation and Simulation format
Journal of Statistical Computation and Simulation is a peer-reviewed journal published by Taylor & Francis, covering Advanced Statistical Methods and Models, Statistical Methods and Inference, Statistical Distribution Estimation and Applications. Over its lifetime it has published 5,925 papers, which have received 73,399 citations.
| Publisher | Taylor & Francis |
|---|---|
| Reference style | Numbered (Vancouver/NLM) Numbered — [1], [2] in the text 1. Smith A, Jones B, Lee C. A representative article title. Journal of Statistical Computation and Simulation. 2023;12(3):45–58.
Formats any DOI in Journal of Statistical Computation and Simulation style. No sign-up. |
| Publishes research in | Advanced Statistical Methods and Models Statistical Methods and Inference Statistical Distribution Estimation and Applications Statistical Methods and Bayesian Inference Bayesian Methods and Mixture Models |
| ISSN | 0094-9655 |
| Citation impact (2-yr) | 1.15 |
| h-index | 95 |
| i10-index | 1,724 |
| Top institutions publishing here | Texas State University |
| Journal website | www.tandfonline.com |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Papers published in Journal of Statistical Computation and Simulation per year
Citation impact of Journal of Statistical Computation and Simulation by publication year
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Most-cited papers in Journal of Statistical Computation and Simulation
The use of the Gibbs sampler with fully conditionally specified models, where the distribution of each variable given the other variables is the starting point, has become a popular method to create imputations in incomplete multivariate data. The theoretical weakness of this approach is that the specified conditional densities can be incompatible, and therefore the…
Several permutation strategies are often possible for tests of individual terms in analysis-of-variance (ANOVA) designs. These include restricted permutations, permutation of whole groups of units, permutation of some form of residuals or some combination of these. It is unclear, especially for complex designs involving random factors, mixed models or nested hierarchies, just which permutation strategy…
Kumaraswamy [Generalized probability density-function for double-bounded random-processes, J. Hydrol. 462 (1980), pp. 79–88] introduced a distribution for double-bounded random processes with hydrological applications. For the first time, based on this distribution, we describe a new family of generalized distributions (denoted with the prefix ‘Kw’) to extend the normal, Weibull, gamma, Gumbel, inverse Gaussian distributions, among…
Normality tests can be classified into tests based on chi-squared, moments, empirical distribution, spacings, regression and correlation and other special tests. This paper studies and compares the power of eight selected normality tests: the Shapiro–Wilk test, the Kolmogorov–Smirnov test, the Lilliefors test, the Cramer–von Mises test, the Anderson–Darling test, the D'Agostino–Pearson test, the Jarque–Bera test…