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Communications in Statistics Case Studies Data Analysis and Applications is a peer-reviewed journal published by Taylor & Francis, covering Statistical Methods and Bayesian Inference, Advanced Statistical Methods and Models, Statistical Methods and Inference.
| 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 Case Studies Data Analysis and Applications 12 (3): 45–58.
Formats any DOI in Communications in Statistics Case Studies Data Analysis and Applications style. No sign-up. |
| Publishes research in | Statistical Methods and Bayesian Inference Advanced Statistical Methods and Models Statistical Methods and Inference Financial Risk and Volatility Modeling Statistical Methods in Clinical Trials |
| ISSN | 2373-7484 |
| Citation impact (2-yr) | 0.39 |
| h-index | 13 |
| i10-index | 23 |
| Total citations | 834 |
| Top institutions publishing here | Democritus University of Thrace |
| 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 new class of unimodal asymmetric distributions is introduced to the unit interval and these distributions are useful for modeling data of percentages, proportions and fractions. Therefore, we propose the unit-half-normal distribution as a contribution to the earlier path and investigate some of its mathematical properties. The maximum likelihood estimator is obtained with a comprehensive…
Time-homogeneous Markov models are widely used tools for analyzing longitudinal data about the progression of a chronic disease over time. There are advantages to modeling the true disease progression as a discrete time stationary Markov chain. However, one limitation of this method is its inability to handle uneven follow-up assessments or skipped visits. A continuous…
Using data on Broadway performances during the recent decade, we investigate the factors relating to the survival of Broadway shows. We assess the special structure of the Broadway season and build our analysis to accommodate this structure. Three modeling approaches are employed: logistic regression, proportional hazards regression, and (log-)linear regression for censored data. All three…
Literature has found that regression of independent (nearly) nonstationary time series could be spurious. We incorporate this idea to examine whether significant regression could be treated as insignificant in some situations. To do so, we conjecture that significant regression could appear significant in some cases but it could become insignificant in some other cases. To…
Generalized autoregressive moving average (GARMA) models are a class of models that was developed for extending the univariate Gaussian ARMA time series model to a flexible observation-driven model for non-Gaussian time series data. This work presents a Bayesian approach for GARMA models with Poisson, binomial, and negative binomial distributions. A simulation study was carried out…
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