Computational Statistics
Overview
Computational Statistics is a scholarly journal that focuses on the development and application of computational methods in statistics. It publishes high-quality research articles, reviews, and case studies that explore innovative techniques, algorithms, and software for analyzing complex data sets. The journal serves as a platform for statisticians, data scientists, and researchers to exchange ideas and advancements in the field of computational statistics.
Details
Details
Abbr.
Comput Stat
Start
1992
End
Continuing
Frequency
Four issues per year
p-ISSN
0943-4062
e-ISSN
1613-9658
Country
Germany
Language
English
Metrics
Metrics
h-index / Ranks: 7207
51
SJR / Ranks: 7979
566
CiteScore / Ranks: 10041
2.30
JIF / Ranks: 6403
1.3
Recent Articles
1.
Treszoks J, Pal S
Comput Stat
. 2025 Feb;
40(1):125-151.
PMID: 40012557
In this paper, we extend the unified class of Box-Cox transformation (BCT) cure rate models to accommodate interval-censored data. The probability of cure is modeled using a general covariate structure,...
2.
Austin P
Comput Stat
. 2025 Feb;
40(2):929-949.
PMID: 39975455
Supplementary Information: The online version contains supplementary material available at 10.1007/s00180-024-01518-w.
3.
Zhang P, Dong T, Liang F
Comput Stat
. 2025 Jan;
39(6):3347-3372.
PMID: 39868364
State estimation for large-scale non-Gaussian dynamic systems remains an unresolved issue, given nonscalability of the existing particle filter algorithms. To address this issue, this paper extends the Langevinized ensemble Kalman...
4.
Pal S, Peng Y, Aselisewine W
Comput Stat
. 2024 Aug;
39(5):2743-2769.
PMID: 39176239
We consider interval censored data with a cured subgroup that arises from longitudinal followup studies with a heterogeneous population where a certain proportion of subjects is not susceptible to the...
5.
Chang C, Ogden R, Chen Y
Comput Stat
. 2024 Jun;
29(6):1497-1513.
PMID: 38912384
In recent years, several methods have been proposed to deal with functional data classification problems (e.g., one-dimensional curves or two- or three-dimensional images). One popular general approach is based on...
6.
Joint Bayesian longitudinal models for mixed outcome types and associated model selection techniques
Seedorff N, Brown G, Scorza B, Petersen C
Comput Stat
. 2024 Jan;
38(4):1735-1769.
PMID: 38292019
Motivated by data measuring progression of leishmaniosis in a cohort of US dogs, we develop a Bayesian longitudinal model with autoregressive errors to jointly analyze ordinal and continuous outcomes. Multivariate...
7.
Tapia A, Gonzalez S, Vergara J, Villafuerte M, Montiel L
Comput Stat
. 2023 Jun;
:1-26.
PMID: 37360995
The interest of this article is to better understand the effects of different public policy alternatives to handle the COVID-19 pandemic. In this work we use the susceptible, infected, recovered...
8.
Rahardiantoro S, Sakamoto W
Comput Stat
. 2023 Jun;
:1-25.
PMID: 37360994
This study addressed the issue of determining multiple potential clusters with regularization approaches for the purpose of spatio-temporal clustering. The generalized lasso framework has flexibility to incorporate adjacencies between objects...
9.
Weisser C, Gerloff C, Thielmann A, Python A, Reuter A, Kneib T, et al.
Comput Stat
. 2023 May;
38(2):647-674.
PMID: 37223721
Topic models are a useful and popular method to find latent topics of documents. However, the short and sparse texts in social media micro-blogs such as Twitter are challenging for...
10.
Rondero-Guerrero C, Gonzalez-Hernandez I, Soto-Campos C
Comput Stat
. 2022 Nov;
:1-24.
PMID: 36405879
A new uniform distribution model, generalized powered uniform distribution (), which is based on incorporating the parameter into the probability density function (pdf) associated with the power of random variable...