{"title":"Martingale posteriors for generative classifiers","authors":"Pier Giovanni Bissiri, Matteo Borrotti","doi":"10.1016/j.spl.2025.110627","DOIUrl":"10.1016/j.spl.2025.110627","url":null,"abstract":"<div><div>Generative models for classification are a well-established method in statistics and machine learning. Martingales posteriors provide a computationally feasible method for performing prior-free Bayesian analysis. This paper aims to address the problem of uncertainty quantification through martingale posteriors for generative models for classification. To this aim, a conditionally identically distributed sequence of observations is considered. An empirical analysis is given.</div></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":"231 ","pages":"Article 110627"},"PeriodicalIF":0.7,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145792040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Lie algebraic duality for some Markov processes","authors":"Sayantan Maitra , Aritra Mandal","doi":"10.1016/j.spl.2025.110624","DOIUrl":"10.1016/j.spl.2025.110624","url":null,"abstract":"<div><div>The framework of Lie algebra has recently been proposed for establishing duals of various Markov processes. We apply this technique to obtain the dual processes of the Feller diffusion and the infinite dimensional interacting Wright-Fisher diffusion.</div></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":"231 ","pages":"Article 110624"},"PeriodicalIF":0.7,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145792039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Extreme values of scaled L-moments","authors":"Tomasz Rychlik , Magdalena Szymkowiak","doi":"10.1016/j.spl.2025.110626","DOIUrl":"10.1016/j.spl.2025.110626","url":null,"abstract":"<div><div>Due to Hosking (1990) (<em>J. R. Stat. Soc. Ser. B Stat. Methodol.</em> <strong>52</strong>, 105–124) all the values of scaled <span><math><mi>L</mi></math></span>-moments belong to the interval <span><math><mrow><mo>(</mo><mo>−</mo><mn>1</mn><mo>,</mo><mn>1</mn><mo>)</mo></mrow></math></span>. We prove that 1 is actually the sharp upper bound for every scaled <span><math><mi>L</mi></math></span>-moment, and <span><math><mrow><mo>−</mo><mn>1</mn></mrow></math></span> is the optimal lower bound for the odd scaled <span><math><mi>L</mi></math></span>-moments. We present a method of determining the optimal lower bounds on even scaled <span><math><mi>L</mi></math></span>-moments, which are located in <span><math><mrow><mo>(</mo><mo>−</mo><mn>1</mn><mo>,</mo><mn>0</mn><mo>)</mo></mrow></math></span>. We also present sharp lower and upper bounds on the <span><math><mi>L</mi></math></span>-moments based on nonnegative samples and measured in the units being the expectations of the parent distributions.</div></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":"231 ","pages":"Article 110626"},"PeriodicalIF":0.7,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Adaptive minimax-optimal Wasserstein deconvolution with unknown error distributions","authors":"Catia Scricciolo","doi":"10.1016/j.spl.2025.110589","DOIUrl":"10.1016/j.spl.2025.110589","url":null,"abstract":"<div><div>We study the problem of deconvolving an unknown distribution function when the error distribution is ordinary smooth and unknown. Using data from an auxiliary experiment that provides information about the error distribution, we establish minimax-optimal convergence rates (up to logarithmic factors) with respect to the 1-Wasserstein metric for a kernel-based distribution function estimator over the full range of Hölder-type classes of densities on <span><math><mi>R</mi></math></span>. Furthermore, we propose a rate-adaptive, data-driven estimation procedure that automatically selects the optimal bandwidth across <span><math><mi>α</mi></math></span>-Hölder-type classes of mixing densities for <span><math><mrow><mi>α</mi><mo>≥</mo><mfrac><mrow><mn>1</mn></mrow><mrow><mn>2</mn></mrow></mfrac></mrow></math></span>, requiring no prior knowledge of the regularity parameters.</div></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":"230 ","pages":"Article 110589"},"PeriodicalIF":0.7,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145529166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cinzia Di Nuzzo, Salvatore Ingrassia, Luca Scaffidi Domianello
{"title":"Fitting mixtures of von Mises distributions via noise contrastive estimation","authors":"Cinzia Di Nuzzo, Salvatore Ingrassia, Luca Scaffidi Domianello","doi":"10.1016/j.spl.2025.110608","DOIUrl":"10.1016/j.spl.2025.110608","url":null,"abstract":"<div><div>Directional distributions requires the evaluation of complicated normalizing constants, even for the univariate von Mises. For this reason, maximum likelihood estimation methods are often difficult to apply in practice. To address this issue, we present an approach based on Noise Contrastive Estimation (NCE), a statistical learning technique used for parameter estimation in non-normalized statistical models. In NCE, the estimation problem is reformulated as a binary classification task. In this paper, we focus on fitting mixtures of von Mises distributions, with particular emphasis on toroidal data. Our application to real data, in which we compare several estimation methods, suggests that NCE is a promising alternative for parameter inference in finite mixtures of directional distributions.</div></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":"230 ","pages":"Article 110608"},"PeriodicalIF":0.7,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145624241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Generalized Likelihood Ratio test for constancy in varying coefficient models with endogenous regressors","authors":"Luis A. Arteaga-Molina, Juan M. Rodriguez-Poo","doi":"10.1016/j.spl.2025.110606","DOIUrl":"10.1016/j.spl.2025.110606","url":null,"abstract":"<div><div>This paper proposes a Generalized Likelihood Ratio test for assessing coefficient constancy in varying coefficient models with endogenous regressors. The test accommodates endogeneity through a nonparametric instrumental variables framework and is explicitly designed for time series data, allowing for serial dependence via mixing conditions.</div></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":"230 ","pages":"Article 110606"},"PeriodicalIF":0.7,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145580284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Mean convergence for the maximum of weighted sums of negatively associated random variables under Gut’s condition","authors":"Lê Vǎn Thành","doi":"10.1016/j.spl.2025.110612","DOIUrl":"10.1016/j.spl.2025.110612","url":null,"abstract":"<div><div>Gut (2004) provided necessary and sufficient conditions for the weak law of large numbers with regularly varying norming sequences. This paper shows that Gut’s conditions are also necessary and sufficient for a mean convergence result for the maximum of the weighted sums. A complement to the main result in Boukhari (2022) is also presented. The sharpness of the main theorems is illustrated by three examples.</div></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":"230 ","pages":"Article 110612"},"PeriodicalIF":0.7,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145693577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"On elephant random walk with random memory","authors":"M. Dhillon, K.K. Kataria","doi":"10.1016/j.spl.2025.110610","DOIUrl":"10.1016/j.spl.2025.110610","url":null,"abstract":"<div><div>In this paper, we introduce the elephant random walk (ERW) with memory consisting of randomly selected steps from its history. It is a time-changed variant of the standard elephant random walk with memory consisting of its full history. At each time point, the time changing component is the composition of two uniformly distributed independent random variables with support over all the past steps. Several conditional distributional properties including the conditional mean increments and conditional displacement of ERW with random memory are obtained. Using these conditional results, we derive the recursive and explicit expressions for the mean increments and mean displacement of the walk.</div></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":"230 ","pages":"Article 110610"},"PeriodicalIF":0.7,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145624243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Large deviations for a subcritical Galton–Watson process with state-dependent immigration","authors":"Doudou Li , Han Liu , Mei Zhang","doi":"10.1016/j.spl.2025.110602","DOIUrl":"10.1016/j.spl.2025.110602","url":null,"abstract":"<div><div>In this paper, we consider a subcritical Galton–Watson branching process with state-dependent immigration <span><math><mi>X</mi></math></span>, where immigration is allowed to enter iff the previous generation was empty. Under the exponential moment conditions of branching and immigration, we obtain the large deviations rate of the total population of <span><math><mi>X</mi></math></span> up to time <span><math><mi>n</mi></math></span>.</div></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":"230 ","pages":"Article 110602"},"PeriodicalIF":0.7,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145624244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"On some properties of a partial ordering based on the mean time to failure function","authors":"Lisa Parveen","doi":"10.1016/j.spl.2025.110621","DOIUrl":"10.1016/j.spl.2025.110621","url":null,"abstract":"<div><div>Various properties of the ordering notion, namely decreasing in mean time to failure (DMTTF) order has been explored. Connections between DMTTF order and other well-known partial orderings of life distributions are established. Interrelationships with certain variability orderings are also explored. The applicability of the results has been demonstrated in the context of coherent systems with dependent but identically distributed components.</div></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":"231 ","pages":"Article 110621"},"PeriodicalIF":0.7,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145786940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}