Australian & New Zealand Journal of Statistics

Papers
(The median citation count of Australian & New Zealand Journal of Statistics is 0. 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 2022-01-01 to 2026-01-01.)
ArticleCitations
Seminal Ideas and Controversies in Statistics. By Roderick J. A.Little, Boca Raton, FL: CRC Press, 2025. 243 pp. AU 10
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Model averaged tail area confidence intervals in nested linear regression models9
Full Bayesian analysis of triple seasonal autoregressive models9
Lower bounds of projection weighted symmetric discrepancy on uniform designs5
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Adjusted Maximum Likelihood Method Based on Shrinkage Factor Bias Reduction for Multivariate Fay–Herriot Model4
A seminal contribution of Ailsa Land and Alison Doig Harcourt to the field of mathematical programming4
4
Functional Data Analysis with R. By C. M.Crainiceanu, J.Goldsmith, A.Leroux, and E.Cui, Boca Raton, FL: Chapman and Hall/CRC. 2024. 338 pages. AU$ 138.40 (hardback). ISBN: 978‐1‐032‐24471‐6.4
Generating Synthetic Data With Locally Estimated Distributions for Disclosure Control3
Simon Christopher Barry, 12 February 1965–16 July 20233
Asymptotics of M‐estimator in multivariate linear regression models for a class of random errors3
Bayesian modelling of effects of prenatal alcohol exposure on child cognition based on data from multiple cohorts3
Robust PCA for high‐dimensional data based on characteristic transformation3
Teaching of Confidence Intervals in Context3
Properties of the affine‐invariant ensemble sampler's ‘stretch move’ in high dimensions3
A method to reduce the width of confidence intervals by using a normal scores transformation3
Simultaneous clustering of individuals and covariates for high‐dimensional longitudinal data2
Issue Information2
High‐dimensional graphical inference via partially penalised regression2
A new minification integer‐valued autoregressive process driven by explanatory variables2
Application of nonparametric approach to extreme value inference in distribution estimation of sample maximum and its properties2
Embedding latent class regression and latent class distal outcome models into cluster‐weighted latent class analysis: a detailed simulation experiment2
Testing multiple dispersion effects from unreplicated order‐of‐addition experiments2
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Short‐term forecasting with a computationally efficient nonparametric transfer function model2
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Measurement errors in semi‐parametric generalised regression models2
Population Size Estimation Using Covariates Having Missing Values and Measurement Error: Estimating Ethnic Group Sizes in New Zealand2
Duncan Standon Ironmonger AM FASSA, 12 October 1931–3 September 20242
Multivariate Kruskal_Wallis tests based on principal component score and latent source of independent component analysis2
Bayesian hierarchical mixture models for detecting non‐normal clusters applied to noisy genomic and environmental datasets2
A calibrated data‐driven approach for small area estimation using big data2
Latent heterogeneity in COVID‐19 hospitalisations: a cluster‐weighted approach to analyse mortality1
Online semiparametric regression via sequential Monte Carlo1
Least‐squares estimators of the linear‐by‐linear association parameter from an ordinal log‐linear model1
A Technology Pilot for Small Group Teaching of Statistics1
Co‐Clustering Analysis of Multi‐Layer Directed Networks: A Spectral Approach1
Efficient estimation of partially linear tail index models using B‐splines1
The role of pairwise matching in experimental design for an incidence outcome1
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A class of kth‐order dependence‐driven random coefficient mixed thinning integer‐valued autoregressive process to analyse epileptic seizure data and COVID‐19 data1
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Examining the Interface Design of Tidyverse1
Penalised, post‐pretest, and post‐shrinkage strategies in nonlinear growth models1
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Model‐Free Local Partial Correlation1
A nonparametric mixture approach to density and null proportion estimation in large‐scale multiple comparison problems1
Normalising Transformation of the Hill Estimator1
Variable selection in heterogeneous panel data models with cross‐sectional dependence1
Exact samples sizes for clinical trials subject to size and power constraints1
Statistical balancing as an unconstrained optimisation problem0
Drayage Routing Problems: A Comprehensive Survey and a New Compact Model0
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Collaboration and Leadership in Teaching Statistics in Higher Education0
Text in R graphics0
Erratum0
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Estimation of Daily Smoking Prevalence for Disaggregated Statistical Areas in Australia0
MPS: An R package for modelling shifted families of distributions0
Autocovariance function estimation via difference schemes for a semiparametric change point model with m$$ m $$‐dependent errors0
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A new robust covariance matrix estimation for high‐dimensional microbiome data0
Detection boundary for a sparse gamma scale mixture model0
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Bayesian hypothesis tests with diffuse priors: Can we have our cake and eat it too?0
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Permutation entropy and its variants for measuring temporal dependence0
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Functional dimension reduction based on fuzzy partition and transformation0
Spline linear mixed‐effects models for causal mediation analysis with longitudinal data0
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Bayesian neural tree models for nonparametric regression0
Global implicit function theorems and the online expectation–maximisation algorithm0
John Newton Darroch, 1930–20240
Forecasting Density‐Valued Functional Panel Data0
On two conjectures about perturbations of the stochastic growth rate0
How data or error covariance can change and still retain BLUEs as well as their covariance or the sum of squares of errors0
A Divide and Conquer Algorithm of Bayesian Density Estimation0
Visual assessment of matrix‐variate normality0
Are Statisticians Sufficiently Engaged With Public Policy?0
Homogeneity and Sparsity Pursuit Using Robust Adaptive Fused Lasso0
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Modelling students’ career indicators via mixtures of parsimonious matrix‐normal distributions0
Distance Measures for Unweighted Undirected Networks: A Comparison Study0
Prediction de‐correlated inference: A safe approach for post‐prediction inference0
Identifying changes in the distribution of income from higher‐order moments with an application to Australia0
Distributional modelling of positively skewed data via the flexible Weibull extension distribution0
Examining collinearities0
Exact testing for heteroscedasticity in a two‐way layout in variety frost trials when incorporating a covariate0
A Festschrift for Alison Harcourt0
Unified robust estimation0
Spying on the prior of the number of data clusters and the partition distribution in Bayesian cluster analysis0
Comparisons of distributions of Australian mental health scores0
The incremental progression from fixed to random factors in the analysis of variance: a new synthesis0
A novel response model and target selection method with applications to marketing0
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Exact likelihoods for N‐mixture models with time‐to‐detection data0
spbal: An R package for spatially balanced master sampling0
Bayesian non‐parametric spatial prior for traffic crash risk mapping: A case study of Victoria, Australia0
Asymptotics for the conditional self‐weighted M$$ M $$ estimator of GRCA(p$$ p $$) models and its statistical inference0
Community Detection and Network Reconstruction With Dependent Connectivity From Rich but Noisy Network Data0
Semi‐supervised Gaussian mixture modelling with a missing‐data mechanism in R0
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Post‐Shrinkage Strategies in Statistical and Machine Learning for High Dimensional Data. By S. E.Ahmed, F.Ahmed, and B.Yüzbaşi, Boca Raton, FL: CRC Press. 2023. 408 pages. AU$ 210.40 (hardback). ISBN:0
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Using R‐Indicators to Address Response Bias: Evidence From the Longitudinal Surveys of Australian Youth0
PanIC: Consistent information criteria for general model selection problems0
Clemens William Pratt, 2 July 1936–16 January 20250
On the diversity of test instances for studying branch‐and‐bound performance0
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Addendum to ‘The Incremental Progression From Fixed to Random Factors in the Analysis of Variance: A New Synthesis’0
Smooth tests of goodness of fit for the distributional assumption of regression models0
Small area estimation under a semi‐parametric covariate measured with error0
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Modal clustering on PPGMMGA projection subspace0
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Automated Residual Plot Assessment With the R Package autovi and the Shiny Application autovi.web0
The place of probability distributions in statistical learning. A commented book review of ‘Distributions for modeling location, scale, and shape using GAMLSS in R’ by Rigby et al. (2021)0
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The multivariate component zero‐inflated Poisson model for correlated count data analysis0
Bayesian analysis of multivariate mixed longitudinal ordinal and continuous data0
Minimum cost‐compression risk in principal component analysis0
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Robust subtractive stability measures for fast and exhaustive feature importance ranking and selection in generalised linear models0
Approximate inferences for Bayesian hierarchical generalised linear regression models0
A Festschrift for Geoff McLachlan0
Circular and spherical projected Cauchy distributions: A novel framework for directional data modelling0
Bernoulli's Fallacy: Statistical Illogic and the Crisis of Modern Science. By AubreyClayton, New York, Columbia University Press, 1st ed., 2021. 368 pages. AU$ 57.95 (hardcover). ISBN: 10:0231199945.0
The Efficiency of Bivariate Fay‐Herriot Small Area Estimators0
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A Richards growth model to predict fruit weight0
Statistical methods for astronomical data analysis. By A. K.Chattopadhyay and T.Chattopadhyay. New York: Springer. 2014. 349 pages. UK£49.99 (hardback). ISBN: 978‐1‐4939‐1506‐4.0
Telling Stories with Data: With Application in R. By RohanAlexander. CRC Press. 2023. 622 pages. AU$129.60 (hardback). ISBN: 978‐1‐0321‐3477‐2.0
Space‐Time Autoregressive Hilbertian Models and Their Application for Wind Speed0
Visualising the pattern of long‐term genotype performance by leveraging a genomic prediction model0
On the selection of predictors by using greedy algorithms and information theoretic criteria0
Sufficient dimension reduction for clustered data via finite mixture modelling0
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