OOIR: Observatory of International Research

Papers

(The TQCC of Scandinavian Journal of Statistics is 3. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2022-08-01 to 2026-08-01.)

Article	Citations
A novel semiparametric approach to nonignorable missing data by catching covariate marginal information	41
On some publications of Sir David Cox	30
	21
Sparse Fréchet sufficient dimension reduction with graphical structure among predictors	15
Asymptotic inference of the ARMA model with time‐functional variance noises	12
Kernel mean embedding of probability measures and its applications to functional data analysis	12
Empirical best prediction of small area bivariate parameters	11
Spectral characteristics of Harmonizable VARMA processes	11
Time‐Varying Degree‐Corrected Stochastic Block Models	11
Editorial	10
Sparse concordance‐based ordinal classification	9
Efficient multiple‐robust estimation for nonresponse data under informative sampling	8
Nonparametric adaptive estimation for interacting particle systems	8
Greenland, S. (2023). Divergence vs. decision P‐values: A distinction worth making in theory and keeping in practice. Scandinavian Journal of Statistics	8
Group Regression With Tailored Penalties for High‐Dimensional Data With or Without Predefined Groups	8
Maximum Spacing Estimation for Multivariate Observations Under a General Class of Information‐Type Measures for Misspecified Models	7
Statistical inference in the presence of imputed survey data through regression trees and random forests	7
Issue Information	7
A new paradigm for high‐dimensional data: Distance‐based semiparametric feature aggregation framework via between‐subject attributes	7
Sparse principal component analysis for high‐dimensional stationary time series	7
Optimal subsampling for estimation of dimension reduction directions	7
Variable selection via thresholding	7
A joint estimation approach for monotonic regression functions in general dimensions	7
Revisiting the sequence symmetry analysis design	7
A Semiparametric Approach for Robust Modeling of Electronic Health Record Linked Biobank Data	7

Estimating absorption time distributions of general Markov jump processes	6
Testing relevant hypotheses in functional variance function via self‐normalization	6
Fixed effects Bayesian testing in high‐dimensional linear mixed models	6
Plug‐in machine learning for partially linear mixed‐effects models with repeated measurements	6
	5
Weighted reduced rank estimators under cointegration rank uncertainty	5
Professor Elja Arjas: A prominent figure in establishing statistics in Finland	5
Mahalanobis balancing: A multivariate perspective on approximate covariate balancing	5
Kernel‐based marginal testing for covariate effects in high‐dimensional settings	5
Lancaster correlation: A new dependence measure linked to maximum correlation	5
On high‐dimensional variance estimation in survey sampling	5
Issue Information	5
Bandwidth selection for kernel intensity estimators for spatial point processes	5
Recursive Bayesian prediction of remaining useful life for gamma degradation process under conjugate priors	4
Selection of linear mixed‐effects models for clustered data	4
Consistent Bayesian information criterion based on a mixture prior for possibly high‐dimensional multivariate linear regression models	4
Semiparametric regression with localized Bregman divergence	4
A Modified Random Survival Forest for Improving Prediction Accuracy in Case‐Cohort and Generalized Case‐Cohort Studies	4
Empirical and instance‐dependent estimation of Markov chain and mixing time	4
A general framework on conditions for constraint‐based causal learning	4
Distorted distributions and ROC curves	4
Likelihood Estimation for Stochastic Differential Equations with Mixed Effects	4
Corrigendum to “Shannon Entropy and Mutual Information for Multivariate Skew‐Elliptical Distributions” published in Scandinavian Journal of Statistics (2013), vol. 40, pp. 42–62	4
On Robustness of Pairwise Kalman Filters	4
Log‐density gradient covariance and automatic metric tensors for Riemann manifold Monte Carlo methods	4
Confidence intervals in monotone regression	4
Construction of maximum projection Latin hypercube designs using number‐theoretic methods	4
Issue Information	4
Deep neural network classifier for multidimensional functional data	4
Consistent covariances estimation for stratum imbalances under minimization method for covariate‐adaptive randomization	4
	4
	4
David J. Olive's contribution to the Discussion of “On optimal linear prediction” by I. Helland	3
Statistical disaggregation—A Monte Carlo approach for imputation under constraints	3
Rolf Sundberg's contribution to the Discussion of “On optimal linear prediction” by I. Helland	3
	3
A special section honoring Nils Lid Hjort	3
Regularized t$$ t $$ distribution: definition, properties, and applications	3
Semiparametric regression for circular response with application in ecology	3
Repelled Point Processes With Application to Numerical Integration	3
Extrapolation estimation for nonparametric regression with measurement error	3
Asymptotic properties of the maximum smoothed partial likelihood estimator in the change‐plane Cox model	3
	3
Connecting simple and precise P‐values to complex and ambiguous realities (includes rejoinder to comments on “Divergence vs. decision P‐values”)	3
Learning under commission and omission event outliers	3
Discussion of “Divergence vs. Decision P$$ P $$‐values: A Distinction Worth Making in Theory and Keeping in Practice – or, How Divergence P$$ P $$‐values Measure Evidence Even When Decision P$$ P $$‐v	3
Issue Information	3
Adjusted location‐invariant U‐tests for the covariance matrix with elliptically high‐dimensional data	3
A proper concordance index for models with crossing hazards	3
Dimension reduction for optimal design problems with Kronecker product structure	3

Nonparametric plug‐in classifier for multiclass classification of S.D.E. paths	3
Nonparametric estimation of path‐specific effects in the presence of nonignorable missing covariates	3
Covariance‐based soft clustering of functional data based on the Wasserstein–Procrustes metric	3