Computational Statistics (CompStat) is an international journal which promotes the publication of applications and methodological research in the field of Computational Statistics. The focus of papers in CompStat is on the contribution to and influence of computing on statistics and vice versa. The journal provides a forum for computer scientists, mathematicians, and statisticians in a variety of fields of statistics such as biometrics, econometrics, data analysis, graphics, simulation, algorithms, knowledge based systems, and Bayesian computing. CompStat publishes hardware, software plus package reports.
《计算统计学》（CompStat）是一份国际期刊，旨在促进计算统计学领域的应用和方法研究的出版。CompStat中的论文的重点是计算对统计的贡献和影响，反之亦然。该杂志为计算机科学家、数学家和统计学家提供了一个论坛，涉及统计学的各个领域，如生物计量学、计量经济学、数据分析、图形、模拟、算法、基于知识的系统和贝叶斯计算。CompStat发布硬件、软件和软件包报告。
fdANOVA: an R software package for analysis of variance for univariate and multivariate functional data
来源期刊：Computational StatisticsDOI：10.1007/S00180-018-0842-7
Time series anomaly detection based on shapelet learning
来源期刊：Computational StatisticsDOI：10.1007/S00180-018-0824-9
Bayesian analysis of Weibull distribution based on progressive type-II censored competing risks data with binomial removals
来源期刊：Computational StatisticsDOI：10.1007/S00180-018-0847-2
Functional data clustering via hypothesis testing k-means
来源期刊：Computational StatisticsDOI：10.1007/S00180-018-0808-9
The performance of latent growth curve model-based structural equation model trees to uncover population heterogeneity in growth trajectories
来源期刊：Computational StatisticsDOI：10.1007/S00180-018-0815-X
Predicting missing values: a comparative study on non-parametric approaches for imputation
来源期刊：Computational StatisticsDOI：10.1007/s00180-019-00900-3
Variable selection in functional additive regression models
来源期刊：Computational StatisticsDOI：10.1007/s00180-018-0844-5
Estimating reducible stochastic differential equations by conversion to a least-squares problem
来源期刊：Computational StatisticsDOI：10.1007/s00180-018-0837-4
An extension of the K-means algorithm to clustering skewed data
来源期刊：Computational StatisticsDOI：10.1007/S00180-018-0821-Z
Mixtures of multivariate restricted skew-normal factor analyzer models in a Bayesian framework
来源期刊：Computational StatisticsDOI：10.1007/S00180-019-00870-6
Robust estimation for spatial autoregressive processes based on bounded innovation propagation representations
来源期刊：Computational StatisticsDOI：10.1007/S00180-018-0845-4
Investigating GQL-based inferential approaches for non-stationary BINAR(1) model under different quantum of over-dispersion with application
来源期刊：Computational StatisticsDOI：10.1007/S00180-018-0836-5
Power comparison for propensity score methods
来源期刊：Computational StatisticsDOI：10.1007/S00180-018-0852-5
Flexible regression modeling for censored data based on mixtures of student-t distributions
来源期刊：Computational StatisticsDOI：10.1007/S00180-018-0856-1
Clustering acoustic emission signals by mixing two stages dimension reduction and nonparametric approaches
来源期刊：Computational StatisticsDOI：10.1007/S00180-018-00864-W
Median constrained bucket order rank aggregation
来源期刊：Computational StatisticsDOI：10.1007/S00180-018-0858-Z
Assessing variable importance in clustering: a new method based on unsupervised binary decision trees
来源期刊：Computational StatisticsDOI：10.1007/S00180-018-0857-0
Fusion learning algorithm to combine partially heterogeneous Cox models
来源期刊：Computational StatisticsDOI：10.1007/s00180-018-0827-6
Four algorithms to construct a sparse kriging kernel for dimensionality reduction
来源期刊：Computational StatisticsDOI：10.1007/S00180-019-00874-2
Classification tree algorithm for grouped variables
来源期刊：Computational StatisticsDOI：10.1007/S00180-019-00894-Y
Neural network gradient Hamiltonian Monte Carlo
来源期刊：Computational StatisticsDOI：10.1007/s00180-018-00861-z
Some new statistical methods for a class of zero-truncated discrete distributions with applications
来源期刊：Computational StatisticsDOI：10.1007/S00180-018-00860-0
On the penalized maximum likelihood estimation of high-dimensional approximate factor model
来源期刊：Computational StatisticsDOI：10.1007/S00180-019-00869-Z
Estimation of random-effects model for longitudinal data with nonignorable missingness using Gibbs sampling
来源期刊：Computational StatisticsDOI：10.1007/S00180-019-00887-X
Clicks and cliques: exploring the soul of the community
来源期刊：Computational StatisticsDOI：10.1007/s00180-019-00881-3
A tale of four cities: exploring the soul of State College, Detroit, Milledgeville and Biloxi
来源期刊：Computational StatisticsDOI：10.1007/S00180-018-00863-X
Community engagement and subgroup meta-knowledge: some factors in the soul of a community
来源期刊：Computational StatisticsDOI：10.1007/S00180-019-00879-X
A multiple-try Metropolis–Hastings algorithm with tailored proposals
来源期刊：Computational StatisticsDOI：10.1007/S00180-019-00878-Y
Estimation of multivariate 3rd moment for high-dimensional data and its application for testing multivariate normality
来源期刊：Computational StatisticsDOI：10.1007/S00180-018-00865-9
Consistency of survey opinions and external data
来源期刊：Computational StatisticsDOI：10.1007/S00180-019-00882-2
Benefits of functional PCA in the analysis of single-trial auditory evoked potentials
来源期刊：Computational StatisticsDOI：10.1007/S00180-018-0819-6
Variable selection in functional additive regression models
来源期刊：Computational StatisticsDOI：10.1007/978-3-319-55846-2_15
Drivers of community attachment: an interactive analysis
来源期刊：Computational StatisticsDOI：10.1007/S00180-018-00862-Y
Probability of misclassification in model-based clustering
来源期刊：Computational StatisticsDOI：10.1007/S00180-019-00868-0
Weighted composite quantile regression for single index model with missing covariates at random
来源期刊：Computational StatisticsDOI：10.1007/S00180-019-00886-Y
Permutation based testing on covariance separability
来源期刊：Computational StatisticsDOI：10.1007/S00180-018-0839-2
A homoscedasticity test for the accelerated failure time model
来源期刊：Computational StatisticsDOI：10.1007/S00180-018-0840-9
Objective Bayesian tests for Fieller–Creasy problem
来源期刊：Computational StatisticsDOI：10.1007/S00180-018-0853-4
An iterative algorithm to bound partial moments
来源期刊：Computational StatisticsDOI：10.1007/S00180-018-0825-8
Bootstrap ICC estimators in analysis of small clustered binary data
来源期刊：Computational StatisticsDOI：10.1007/S00180-019-00885-Z
A note on parallel sampling in Markov graphs
来源期刊：Computational StatisticsDOI：10.1007/S00180-019-00880-4
Bagging of density estimators
来源期刊：Computational StatisticsDOI：10.1007/S00180-019-00889-9
Model-based INAR bootstrap for forecasting INAR(p) models
来源期刊：Computational StatisticsDOI：10.1007/s00180-019-00902-1
Approximate Bayesian computation for Lorenz curves from grouped data
来源期刊：Computational StatisticsDOI：10.1007/s00180-018-0831-x
Pseudo-Bayesian D-optimal designs for longitudinal Poisson mixed models with correlated errors
来源期刊：Computational StatisticsDOI：10.1007/S00180-018-0834-7
Bayesian model-based clustering for longitudinal ordinal data
来源期刊：Computational StatisticsDOI：10.1007/S00180-019-00872-4
Spatio-temporal change of support modeling with R
来源期刊：Computational StatisticsDOI：10.1007/S00180-020-01029-4
Weighted multiple testing procedure for grouped hypotheses with k-FWER control
来源期刊：Computational StatisticsDOI：10.1007/S00180-018-0833-8
Computation of the expected value of a function of a chi-distributed random variable
来源期刊：Computational StatisticsDOI：10.1007/s00180-020-01005-y
Greedy clustering of count data through a mixture of multinomial PCA
来源期刊：Computational StatisticsDOI：10.1007/s00180-020-01008-9
