{"title":"The integrated absolute error of the kernel error distribution estimator in the first-order autoregression model","authors":"Fuxia Cheng","doi":"10.1016/j.spl.2024.110215","DOIUrl":"10.1016/j.spl.2024.110215","url":null,"abstract":"<div><p>This paper considers convergence rates of kernel estimators of the error cumulative distribution function in the first-order autoregressive model. LIL is extended to the integrated absolute error of residual-based kernel error cumulative distribution function estimator.</p></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141853725","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 variation of constant formula for Caputo–Hadamard fractional stochastic differential equations⋆","authors":"Min Li , Chengming Huang , Nan Wang","doi":"10.1016/j.spl.2024.110216","DOIUrl":"10.1016/j.spl.2024.110216","url":null,"abstract":"<div><p>This paper studies the existence and uniqueness of the mild solutions of Caputo–Hadamard fractional stochastic differential equations (SDEs). Subsequently, a variation of constants formula is derived for these equations. The primary proof techniques rely on Itô’s isometry, the martingale representation theorem, and the adaptation of the variation of constants formula employed in deterministic Caputo–Hadamard fractional differential equations (FDEs). Furthermore, we employ the constant variation formula to investigate the mean-square stability of a class of scalar Caputo–Hadamard fractional SDEs and provide stability criteria. Consequently, this class of scalar equations can serve as basic test equations to study the stability of numerical methods for Caputo–Hadamard fractional SDEs.</p></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2024-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141638962","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":"Model selection by pathwise marginal likelihood thresholding","authors":"Claudia Di Caterina , Davide Ferrari","doi":"10.1016/j.spl.2024.110214","DOIUrl":"10.1016/j.spl.2024.110214","url":null,"abstract":"<div><p>We suggest to estimate a sparse parameter vector in multivariate models through the selection of marginal likelihoods from a potentially large set. The resulting estimator involves an adaptive thresholding mechanism, whereby the marginal estimates are set to zero according to their sequential contribution to the joint information computed along a path of increasingly complex models. The effectiveness of our proposal is illustrated via simulations.</p></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141714356","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":"Limiting behavior of a kindness model","authors":"Nicolas Lanchier , Max Mercer","doi":"10.1016/j.spl.2024.110205","DOIUrl":"10.1016/j.spl.2024.110205","url":null,"abstract":"<div><p>This paper is concerned with a stochastic model for the spread of kindness across a social network. Individuals are located on the vertices of a general finite connected graph, and are characterized by their kindness belief. Each individual, say <span><math><mi>x</mi></math></span>, interacts with each of its neighbors, say <span><math><mi>y</mi></math></span>, at rate one. The interactions can be kind or unkind, with kind interactions being more likely when the kindness belief of the sender <span><math><mi>x</mi></math></span> is high. In addition, kind interactions increase the kindness belief of the recipient <span><math><mi>y</mi></math></span>, whereas unkind interactions decrease its kindness belief. The system also depends on two parameters modeling the impact of kind and unkind interactions, respectively. We prove that, when kind interactions have a larger impact than unkind interactions, the system converges to the purely kind configuration with probability tending to one exponentially fast in the large population limit.</p></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141622341","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":"Further results involving residual and past extropy with their applications","authors":"Mohamed Kayid","doi":"10.1016/j.spl.2024.110201","DOIUrl":"10.1016/j.spl.2024.110201","url":null,"abstract":"<div><p>In this paper we have investigated some stochastic aspects of residual extropy and past extropy. We then apply the results to the context of order statistics, coherent systems and record values. Nonparametric estimators for residual extropy and past extropy were introduced and their performance was illustrated using simulated data sets and real data sets.</p></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2024-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141622301","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":"Complete qth moment convergence of moving average processes for m-widely acceptable random variables under sub-linear expectations","authors":"Mingzhou Xu, Xuhang Kong","doi":"10.1016/j.spl.2024.110203","DOIUrl":"https://doi.org/10.1016/j.spl.2024.110203","url":null,"abstract":"<div><p>In this article, we studied complete <span><math><mi>q</mi></math></span>th moment convergence of the moving average processes produced by <span><math><mi>m</mi></math></span>-widely acceptable (<span><math><mi>m</mi></math></span>-WA) random variables under sub-linear expectations. The results here extend those of the moving average processes generated by <span><math><mi>m</mi></math></span>-WOD random variables in probability.</p></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2024-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141605061","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":"Nonparametric estimation for periodic stochastic differential equations driven by G-Brownian motion","authors":"Xuekang Zhang , Chengzhe Huang , Shounian Deng","doi":"10.1016/j.spl.2024.110202","DOIUrl":"https://doi.org/10.1016/j.spl.2024.110202","url":null,"abstract":"<div><p>The paper is concerned with the nonparametric estimation problem for periodic stochastic differential equations driven by <span><math><mi>G</mi></math></span>-Brownian motion based on continuous observations. The consistency and asymptotic distribution of the nonparametric estimator are discussed. Computer simulations are performed to illustrate our theory.</p></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2024-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141605060","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 integrals of birth–death processes at random time","authors":"P. Vishwakarma, K.K. Kataria","doi":"10.1016/j.spl.2024.110204","DOIUrl":"https://doi.org/10.1016/j.spl.2024.110204","url":null,"abstract":"<div><p>In this paper, we consider a time-changed path integral of the homogeneous birth–death process. Here, the time changes according to an inverse stable subordinator. It is shown that its joint distribution with the time-changed birth–death process is governed by a fractional partial differential equation. In a linear case, the explicit expressions for the Laplace transform of their joint generating function, means, variances and covariance are obtained. The limiting behavior of this integral process has been studied. Later, we consider the fractional integrals of linear birth–death processes and their time-changed versions. The mean values of these fractional integrals are obtained and analyzed. In a particular case, it is observed that the time-changed path integral of the linear birth–death process and the fractional integral of time-changed linear birth–death process have equal mean growth.</p></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141582376","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":"Total variation convergence preserves conditional independence","authors":"Steffen Lauritzen","doi":"10.1016/j.spl.2024.110200","DOIUrl":"https://doi.org/10.1016/j.spl.2024.110200","url":null,"abstract":"<div><p>This note establishes that if a sequence <span><math><mrow><msub><mrow><mi>P</mi></mrow><mrow><mi>n</mi></mrow></msub><mo>,</mo><mi>n</mi><mo>=</mo><mn>1</mn><mo>,</mo><mo>…</mo></mrow></math></span> of probability measures converges in total variation to the limiting probability measure <span><math><mi>P</mi></math></span>, and <span><math><mi>σ</mi></math></span>-algebras <span><math><mi>A</mi></math></span> and <span><math><mi>B</mi></math></span> are conditionally independent given <span><math><mi>H</mi></math></span> with respect to <span><math><msub><mrow><mi>P</mi></mrow><mrow><mi>n</mi></mrow></msub></math></span> for all <span><math><mi>n</mi></math></span>, then they are also conditionally independent with respect to the limiting measure <span><math><mi>P</mi></math></span>. As a corollary, this also extends to pointwise convergence of densities to a density.</p></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S016771522400169X/pdfft?md5=c56dd1436844d549837b401ab4b369b9&pid=1-s2.0-S016771522400169X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141542315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Branching processes with immigration in a random environment—The Grincevičius–Grey setup","authors":"Péter Kevei","doi":"10.1016/j.spl.2024.110199","DOIUrl":"https://doi.org/10.1016/j.spl.2024.110199","url":null,"abstract":"<div><p>We determine the tail asymptotics of the stationary distribution of a branching process with immigration in a random environment, when the immigration distribution dominates the offspring distribution. The assumptions are the same as in the Grincevičius–Grey theorem for the stochastic recurrence equation.</p></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141542405","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}