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Communications in Statistics is a peer-reviewed journal published by Taylor & Francis, covering Advanced Statistical Methods and Models, Statistical Distribution Estimation and Applications, Bayesian Methods and Mixture Models.
| Publisher | Taylor & Francis |
|---|---|
| Reference style | Author–year (Chicago, T&F) Author–year — (Smith, 2023) in the text Smith, Ada, Ben Jones, and Cara Lee. 2023. "A Representative Article Title." Communications in Statistics 12 (3): 45–58.
Formats any DOI in Communications in Statistics style. No sign-up. |
| Publishes research in | Advanced Statistical Methods and Models Statistical Distribution Estimation and Applications Bayesian Methods and Mixture Models Statistical Methods and Inference Optimal Experimental Design Methods |
| ISSN | 0090-3272 |
| h-index | 34 |
| i10-index | 97 |
| Total citations | 11,899 |
| Top institutions publishing here | Southern Methodist University |
| Journal website | www.tandfonline.com |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
A method for identifying clusters of points in a multidimensional Euclidean space is described and its application to taxonomy considered. It reconciles, in a sense, two different approaches to the investigation of the spatial relationships between the points, viz., the agglomerative and the divisive methods. A graph, the shortest dendrite of Florek etal. (1951a), is…
An algorithm is given for selacting the biasing paramatar, k, in RIDGE regrassion. By means of simulaction it is shown that the algorithm has the following properties: (i) it produces an aberaged squared error for the regrassion coafficiants that is les than least squares, (ii) the distribuction of squared arrots for the regression coafficiants has…
The cross validation mean square error technique is used to determine the correct degree of smoothing, in fitting smoothing solines to discrete, noisy observations from some unknown smooth function. Monte Cario results snow amazing success in estimating the true smooth function as well as its derivative.
Abstract A multivariate generalization of the farlie-Gumbel-Morgenstern bivariate system of distribution is described. Certain properties, particularly those concerning orthant dependence, are investigated. Keywords: systems of distributionsFarlie-Gumbel-Morgenstern distributionsmultivariate distributionshazard rateorthant dapendence
