English
Related papers

Related papers: Simultaneous confidence bands for Yule-Walker esti…

200 papers

We propose kernel estimator for the distribution function of unobserved errors in autoregressive time series, based on residuals computed by estimating the autoregressive coefficients with the Yule-Walker method. Under mild assumptions, we…

Statistics Theory · Mathematics 2014-05-26 Jiangyan Wang , Rong Liu , Fuxia Cheng , Lijian Yang

The maximum ${\log}_q$ likelihood estimation method is a generalization of the known maximum $\log$ likelihood method to overcome the problem for modeling non-identical observations (inliers and outliers). The parameter $q$ is a tuning…

Methodology · Statistics 2020-12-16 Mehmet Niyazi Çankaya , Roberto Vila

The Bradley-Terry-Luce (BTL) model is a benchmark model for pairwise comparisons between individuals. Despite recent progress on the first-order asymptotics of several popular procedures, the understanding of uncertainty quantification in…

Statistics Theory · Mathematics 2022-08-11 Chao Gao , Yandi Shen , Anderson Y. Zhang

We propose simultaneous confidence bands of the hyperbolic-type for the contrasts between several nonlinear (curvilinear) regression curves. The critical value of a confidence band is determined from the distribution of the maximum of a…

Statistics Theory · Mathematics 2017-01-11 Xiaolei Lu , Satoshi Kuriki

The problem of simultaneous estimation of location/scale parameters $\theta_1$ and $\theta_2$ of a general bivariate location/scale model, when the ordering between the parameters is known apriori (say, $\theta_1\leq \theta_2$), has been…

Statistics Theory · Mathematics 2023-01-03 Naresh Garg , Neeraj Misra

We propose confidence sequences -- sequences of confidence intervals which are valid uniformly over time -- for quantiles of any distribution over a complete, fully-ordered set, based on a stream of i.i.d. observations. We give methods both…

Statistics Theory · Mathematics 2022-07-08 Steven R. Howard , Aaditya Ramdas

Weibull distribution has received a wide range of applications in engineering and science. The utility and usefulness of an estimator is highly subject to the field of practitioner's study. In practice users looking for their desired…

Computation · Statistics 2019-02-18 Sahar Sadani , Kamel Abdollahnezhad , Mahdi Teimouri , Vahid Ranjbar

We study the problem of model selection type aggregation with respect to the Kullback-Leibler divergence for various probabilistic models. Rather than considering a convex combination of the initial estimators $f_1, \ldots, f_N$, our…

Statistics Theory · Mathematics 2016-01-22 Cristina Butucea , Jean-François Delmas , Anne Dutfoy , Richard Fischer

We generalize standard credal set models for imprecise probabilities to include higher order credal sets -- confidences about confidences. In doing so, we specify how an agent's higher order confidences (credal sets) update upon observing…

Statistics Theory · Mathematics 2021-07-20 Justus Hibshman , Tim Weninger

In this work, we revisit the estimation of the model parameters of a Weibull distribution based on iid observations, using the maximum likelihood estimation (MLE) method which does not yield closed expressions of the estimators. Among other…

Computation · Statistics 2025-01-22 Buu-Chau Truong , Peter Mphekgwana , Nabendu Pal

We consider component-wise estimation of order restricted location/scale parameters $\theta_1$ and $\theta_2$ ($\theta_1\leq \theta_2$) of a general bivariate distribution under the squared error loss function. To find improvements over the…

Statistics Theory · Mathematics 2022-07-05 Naresh Garg , Neeraj Misra

We consider optimal sequential allocation in the context of the so-called stochastic multi-armed bandit model. We describe a generic index policy, in the sense of Gittins [J. R. Stat. Soc. Ser. B Stat. Methodol. 41 (1979) 148-177], based on…

We study the $K$-Max combinatorial multi-armed bandits problem with continuous outcome distributions and weak value-index feedback: each base arm has an unknown continuous outcome distribution, and in each round the learning agent selects…

Machine Learning · Computer Science 2025-02-20 Yu Chen , Siwei Wang , Longbo Huang , Wei Chen

Uniform and nonuniform Berry--Esseen (BE) bounds of optimal orders on the closeness to normality for general abstract nonlinear statistics are given, which are then used to obtain optimal bounds on the rate of convergence in the delta…

Statistics Theory · Mathematics 2017-01-17 Iosif Pinelis , Raymond Molzon

We study the maximum likelihood estimator of density of $n$ independent observations, under the assumption that it is well approximated by a mixture with a large number of components. The main focus is on statistical properties with respect…

Statistics Theory · Mathematics 2017-01-19 Arnak S. Dalalyan , Mehdi Sebbar

Let $X_1,X_2,...$ be independent identically distributed random variables with $\mathbb E X_k=0$, $\mathrm{Var} X_k=1$. Suppose that $\varphi(t):=\log \mathbb E e^{t X_k}<\infty$ for all $t>-\sigma_0$ and some $\sigma_0>0$. Let…

Probability · Mathematics 2014-03-11 Zakhar Kabluchko , Yizao Wang

There are essentially three kinds of approaches to Uncertainty Quantification (UQ): (A) robust optimization, (B) Bayesian, (C) decision theory. Although (A) is robust, it is unfavorable with respect to accuracy and data assimilation. (B)…

We study the problem of estimating a distribution over a finite alphabet from an i.i.d. sample, with accuracy measured in relative entropy (Kullback-Leibler divergence). While optimal bounds on the expected risk are known, high-probability…

Statistics Theory · Mathematics 2026-02-27 Jaouad Mourtada

The distribution of the spacing, or the difference between consecutive order statistics, is known only for uniform and exponential random variates. We add here logistic and Gumbel variates, and present an estimator for distributions with a…

Methodology · Statistics 2026-01-30 Greg Kreider

Upper Confidence Bound (UCB) is arguably the most commonly used method for linear multi-arm bandit problems. While conceptually and computationally simple, this method highly relies on the confidence bounds, failing to strike the optimal…

Machine Learning · Computer Science 2020-06-05 Kaige Yang , Laura Toni
‹ Prev 1 2 3 10 Next ›