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We study two nonparametric tests of the hypothesis that a sequence of independent observations is identically distributed against the alternative that at a single change point the distribution changes. The tests are based on the Cramer-von…

Statistics Theory · Mathematics 2020-10-15 Rasmus Erlemann , Richard Lockhart , Rihan Yao

In the common time series model $X_{i,n} = \mu (i/n) + \varepsilon_{i,n}$ with non-stationary errors we consider the problem of detecting a significant deviation of the mean function $\mu$ from a benchmark $g (\mu )$ (such as the initial…

Statistics Theory · Mathematics 2020-05-25 Holger Dette , Florian Heinrichs

Diffusion models, which convert noise into new data instances by learning to reverse a diffusion process, have become a cornerstone in contemporary generative modeling. In this work, we develop non-asymptotic convergence theory for a…

Machine Learning · Computer Science 2024-08-06 Gen Li , Yuting Wei , Yuejie Chi , Yuxin Chen

This paper introduces a quasi-likelihood ratio testing procedure for diffusion processes observed under nonsynchronous sampling schemes. High-frequency data, particularly in financial econometrics, are often recorded at irregular time…

Statistics Theory · Mathematics 2025-03-25 Teppei Ogihara , Futo Ueno

We study a stylized multiple testing problem where the test statistics are independent and assumed to have the same distribution under their respective null hypotheses. We first show that, in the normal means model where the test statistics…

Statistics Theory · Mathematics 2016-04-27 Ery Arias-Castro , Shiyun Chen

We consider parametric estimation for ergodic diffusion processes with noisy sampled data based on the hybrid method, that is, the multi-step estimation with the initial Bayes type estimators. In order to select proper initial values for…

Statistics Theory · Mathematics 2018-12-19 Yusuke Kaino , Shogo H. Nakakita , Masayuki Uchida

We consider parametric estimation of the continuous part of a class of ergodic diffusions with jumps based on high-frequency samples. Various papers previously proposed threshold based methods, which enable us to distinguish whether…

Methodology · Statistics 2019-10-02 Hiroki Masuda , Yuma Uehara

We develop asymptotic theory for weighted likelihood estimators (WLE) under two-phase stratified sampling without replacement. We also consider several variants of WLEs involving estimated weights and calibration. A set of empirical process…

Statistics Theory · Mathematics 2013-04-09 Takumi Saegusa , Jon A. Wellner

We consider nonparametric testing in a non-asymptotic framework. Our statistical guarantees are exact in the sense that Type I and II errors are controlled for any finite sample size. Meanwhile, one proposed test is shown to achieve minimax…

Statistics Theory · Mathematics 2017-02-07 Yun Yang , Zuofeng Shang , Guang Cheng

We extend a recently established asymptotic normality theorem for generalized linear mixed models to include the dispersion parameter. The new results show that the maximum likelihood estimators of all model parameters have asymptotically…

Statistics Theory · Mathematics 2022-08-11 Aishwarya Bhaskaran , Matt P. Wand

We propose a new conditional dependence measure and a statistical test for conditional independence. The measure is based on the difference between analytic kernel embeddings of two well-suited distributions evaluated at a finite set of…

Machine Learning · Statistics 2022-06-17 Meyer Scetbon , Laurent Meunier , Yaniv Romano

Asymptotic local equivalence in the sense of Le Cam is established for inference on the drift in multidimensional ergodic diffusions and an accompanying sequence of Gaussian shift experiments. The nonparametric local neighbourhoods can be…

Statistics Theory · Mathematics 2012-08-20 Arnak Dalalyan , Markus Reiss

We are interested to detect periodic signals in Hilbert space valued time series when the length of the period is unknown. A natural test statistic is the maximum Hilbert-Schmidt norm of the periodogram operator over all fundamental…

Statistics Theory · Mathematics 2020-07-07 Clément Cerovecki , Vaidotas Characiejus , Siegfried Hörmann

This paper explores hypothesis testing for the parametric forms of the mean and variance functions in regression models under diverging-dimension settings. To mitigate the curse of dimensionality, we introduce weighted residual empirical…

Statistics Theory · Mathematics 2025-10-28 Falong Tan , Xu Guo , Lixing Zhu

In this paper, in order to test whether changes have occurred in a nonlinear parametric regression, we propose a nonparametric method based on the empirical likelihood. Firstly, we test the null hypothesis of no-change against the…

Statistics Theory · Mathematics 2014-05-22 Gabriela Ciuperca , Zahraa Salloum

The problems of the construction of the asymptotically distribution free goodness-of-fit tests for three models of stochastic processes are considered. The null hypothesis for all models is composite parametric. All tests are based on the…

Statistics Theory · Mathematics 2014-04-01 Yury A. Kutoyants

This paper establishes the asymptotic independence between the quadratic form and maximum of a sequence of independent random variables. Based on this theoretical result, we find the asymptotic joint distribution for the quadratic form and…

Methodology · Statistics 2023-08-03 Dachuan Chen , Decai Liang , Long Feng

In this paper, our interest is in the problem of simultaneous hypothesis testing when the test statistics corresponding to the individual hypotheses are possibly correlated. Specifically, we consider the case when the test statistics…

Statistics Theory · Mathematics 2019-01-14 Anupam Kundu , Subir Kumar Bhandari

We treat the change point problem in ergodic diffusion processes from discrete observations. Tonaki et al. (2020) proposed adaptive tests for detecting changes in the diffusion and drift parameters in ergodic diffusion models. When any…

Statistics Theory · Mathematics 2021-02-16 Yozo Tonaki , Yusuke Kaino , Masayuki Uchida

The mean absolute deviation about the mean is an alternative to the standard deviation for measuring dispersion in a sample or in a population. For stationary, ergodic time series with a finite first moment, an asymptotic expansion for the…

Methodology · Statistics 2014-06-18 Johan Segers