Australian and New Zealand Journal of Statistics This is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.

On two conjectures about perturbations of the stochastic growth rate
SummaryThe stochastic growth rate describes long-run growth of a population that lives in a fluctuating environment. Perturbation analysis of the stochastic growth rate provides crucial information for population managers, ecologists and evolutionary biologists. This analysis quantifies the response of the stochastic growth rate to changes in demographic parameters. A form of this analysis deals with changes that only occur in some environmental states. Caswell put forth two conjectures about environment-specific perturbations of the stochastic growth rate. The conjectures link the stationary distribution of the stochastic...
Source: Australian and New Zealand Journal of Statistics - February 16, 2023 Category: Statistics Authors: Stefano Giaimo Tags: Original Article Source Type: research

Variable selection in heterogeneous panel data models with cross ‐sectional dependence
AbstractThis paper studies the Bridge estimator for a high-dimensional panel data model with heterogeneous varying coefficients, where the random errors are assumed to be serially correlated and cross-sectionally dependent. We establish oracle efficiency and the asymptotic distribution of the Bridge estimator, when the number of covariates increases to infinity with the sample size in both dimensions. A BIC-type criterion is also provided for tuning parameter selection. We further generalise the marginal Bridge estimator for our model to asymptotically correctly identify the covariates with zero coefficients even when the ...
Source: Australian and New Zealand Journal of Statistics - February 16, 2023 Category: Statistics Authors: Xiaoling Mei, Bin Peng, Huanjun Zhu Tags: Original Article Source Type: research

Issue Information
(Source: Australian and New Zealand Journal of Statistics)
Source: Australian and New Zealand Journal of Statistics - January 12, 2023 Category: Statistics Tags: Issue Information Source Type: research

A Richards growth model to predict fruit weight
SummaryThe Richards model comprises several popular sigmoidal and monomolecular growth curves. We illustrate fitting of a Bayesian Richards model by splitting the full growth model into several submodels, followed by a model selection procedure. The performance of the methodology is evaluated by Monte Carlo simulations. A double-sigmoidal version of the Richards model is applied to model grape bunch weight based on data from a New Zealand vineyard over a single growing period.A Bayesian Richards growth model applied to grape size data. Representations of phenological processes are selected through multi-model inference. (S...
Source: Australian and New Zealand Journal of Statistics - January 5, 2023 Category: Statistics Authors: Daniel Gerhard, Elena Moltchanova Tags: Original Article Source Type: research

A new minification integer ‐valued autoregressive process driven by explanatory variables
SummaryThe discrete minification model based on the modified negative binomial operator, as an extension to the continuous minification model, can be used to describe an extreme value after few increasing values. To make this model more practical and flexible, a new minification integer-valued autoregressive process driven by explanatory variables is proposed. Ergodicity of the new process is discussed. The estimators of the unknown parameters are obtained via the conditional least squares and conditional maximum likelihood methods, and the asymptotic properties are also established. A testing procedure for checking existe...
Source: Australian and New Zealand Journal of Statistics - December 29, 2022 Category: Statistics Authors: Lianyong Qian, Fukang Zhu Tags: Original Article Source Type: research

Minimum cost ‐compression risk in principal component analysis
SummaryPrincipal Component Analysis (PCA) is a popular multivariate analytic tool which can be used for dimension reduction without losing much information. Data vectors containing a large number of features arriving sequentially may be correlated with each other. An effective algorithm for such situations is online PCA. Existing Online PCA research works revolve around proposing efficient scalable updating algorithms focusing on compression loss only. They do not take into account the size of the dataset at which further arrival of data vectors can be terminated and dimension reduction can be applied. It is well known tha...
Source: Australian and New Zealand Journal of Statistics - December 28, 2022 Category: Statistics Authors: Bhargab Chattopadhyay, Swarnali Banerjee Tags: Original Article Source Type: research

Small area estimation under a semi ‐parametric covariate measured with error
SummaryIn recent years, small area estimation has played an important role in statistics as it deals with the problem of obtaining reliable estimates for parameters of interest in areas with small or even zero sample sizes corresponding to population sizes. Nested error linear regression models are often used in small area estimation assuming that the covariates are measured without error and also the relationship between covariates and response variable is linear. Small area models have also been extended to the case in which a linear relationship may not hold, using penalised spline (P-spline) regression, but assuming th...
Source: Australian and New Zealand Journal of Statistics - December 9, 2022 Category: Statistics Authors: Reyhane Sefidkar, Mahmoud Torabi, Amir Kavousi Tags: Original Article Source Type: research

Permutation entropy and its variants for measuring temporal dependence
SummaryPermutation entropy (PE) is an ordinal-based non-parametric complexity measure for studying the temporal dependence structure in a linear or non-linear time series. Based on the PE, we propose a new measure, namely permutation dependence (PD), to quantify the strength of the temporal dependence in a univariate time series and remedy the major drawbacks of PE. We demonstrate that the PE and PD are viable and useful alternatives to conventional temporal dependence measures, such as the autocorrelation function (ACF) and mutual information (MI). Compared to the ACF, the PE and PD are not restricted in detecting the lin...
Source: Australian and New Zealand Journal of Statistics - December 9, 2022 Category: Statistics Authors: Xin Huang, Han Lin Shang, David Pitt Tags: Original Article Source Type: research

Issue Information
(Source: Australian and New Zealand Journal of Statistics)
Source: Australian and New Zealand Journal of Statistics - October 17, 2022 Category: Statistics Tags: Issue Information Source Type: research

Multivariate Kruskal_Wallis tests based on principal component score and latent source of independent component analysis
SummaryAnalysing multivariate and high_dimensional multi_sample data is essential in many scientific fields. One of the most crucial and popular topics in modern nonparametric statistics is multi_sample comparison problems for such multivariate and high_dimensional data. The Kruskal_Wallis test is widely used in the multi_sample problem. For multivariate or high_dimensional data, it is imperative to specify how to determine the ranks of individual vector_valued observations in terms of various distance metrics. Alternatively, one can combine the concept of principal component scores or independent component scores with the...
Source: Australian and New Zealand Journal of Statistics - October 17, 2022 Category: Statistics Authors: Amitava Mukherjee, Hidetoshi Murakami Tags: Original Article Source Type: research

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)
AbstractGeneralised additive models for location, scale and shape (GAMLSS) is a type of distributional regression framework that enables modelling numeric dependent variables via probability distributions other than those of the exponential family. While the cogs behind GAMLSS are provided in Stasinopouloset al. 2017's book ‘Flexible regression and smoothing using GAMLSS in R, the new book by Rigbyet al. considers the distributions implemented in the R software that are usable for GAMLSS modelling. A commented summary of that second book is provided in a supplementary file. Unlike traditional book reviews, two topics in ...
Source: Australian and New Zealand Journal of Statistics - September 23, 2022 Category: Statistics Authors: Fernando Marmolejo ‐Ramos, Raydonal Ospina, Freddy Hernández‐Barajas Tags: Original Article Source Type: research

Penalised, post ‐pretest, and post‐shrinkage strategies in nonlinear growth models
SummaryIn nonlinear growth models, we considered the parameter estimation under subspace information for low-dimensional and high-dimensional data. We proposed novel estimators based on pretest and shrinkage strategies to improve the estimation efficiency and to establish asymptotic properties. We used simulation studies and a real data example to confirm the theoretical results. We also applied two well-known penalised methods —least absolute shrinkage and selection operator (LASSO) and adaptive LASSO (aLASSO)—for the dimensional reduction of the predictor variables. The results demonstrated that the pretest and shrin...
Source: Australian and New Zealand Journal of Statistics - September 5, 2022 Category: Statistics Authors: Janjira Piladaeng, S. Ejaz Ahmed, Supranee Lisawadi Tags: Original Article Source Type: research

Robust subtractive stability measures for fast and exhaustive feature importance ranking and selection in generalised linear models
AbstractWe introduce the relatively new concept of subtractive lack-of-fit measures in the context of robust regression, in particular in generalised linear models. We devise a fast and robust feature selection framework for regression that empirically enjoys better performance than other selection methods while remaining computationally feasible when fully exhaustive methods are not. Our method builds on the concepts of model stability, subtractive lack-of-fit measures and repeated model identification. We demonstrate how the multiple implementations add value in a robust regression type context, in particular through uti...
Source: Australian and New Zealand Journal of Statistics - September 2, 2022 Category: Statistics Authors: Connor Smith, Boris Guennewig, Samuel Muller Tags: Original Article Source Type: research

Multivariate Kruskal –Wallis tests based on principal component score and latent source of independent component analysis
SummaryAnalysing multivariate and high-dimensional multi-sample data is essential in many scientific fields. One of the most crucial and popular topics in modern nonparametric statistics is multi-sample comparison problems for such multivariate and high-dimensional data. The Kruskal –Wallis test is widely used in the multi-sample problem. For multivariate or high-dimensional data, it is imperative to specify how to determine the ranks of individual vector-valued observations in terms of various distance metrics. Alternatively, one can combine the concept of principal componen t scores or independent component scores with...
Source: Australian and New Zealand Journal of Statistics - August 4, 2022 Category: Statistics Authors: Amitava Mukherjee, Hidetoshi Murakami Tags: Original Article Source Type: research

A Festschrift for Geoff McLachlan
This article introduces a special issue of the Australian and New Zealand Journal of Statistics, dedicated as a Festschrift for Geoff McLachlan on the occasion of his 75th birthday. (Source: Australian and New Zealand Journal of Statistics)
Source: Australian and New Zealand Journal of Statistics - August 2, 2022 Category: Statistics Authors: Hien Nguyen, Sharon Lee, Florence Forbes Tags: Invited Review Source Type: research