Zobrazeno 1 - 10
of 44 760
pro vyhledávání: '"Mathematics & Statistics"'
Autor:
Chen, Songliang, Han, Fang
This paper examines the limiting variance of nearest neighbor matching estimators for average treatment effects with a fixed number of matches. We present, for the first time, a closed-form expression for this limit. Here the key is the establishment
Externí odkaz:
http://arxiv.org/abs/2411.05758
Autor:
Bayramoglu, Ismihan, Ersin, Pelin
The local dependence function is important in many applications of probability and statistics. We extend the bivariate local dependence function introduced by Bairamov and Kotz (2000) and further developed by Bairamov et al. (2003) to three-variate a
Externí odkaz:
http://arxiv.org/abs/2411.05512
In the usual statistical inference problem, we estimate an unknown parameter of a statistical model using the information in the random sample. A priori information about the parameter is also known in several real-life situations. One such informati
Externí odkaz:
http://arxiv.org/abs/2411.05487
Autor:
Hoessly, Linard
In 2017, Hughes claimed an equivalence between Tjurs $R^2$ coefficient of discrimination and Youden index for assessing diagnostic test performance on $2\times 2$ contingency tables. We prove an impossibility result when averaging over binary outcome
Externí odkaz:
http://arxiv.org/abs/2411.05391
We study in this paper the problem of least absolute deviation (LAD) regression for high-dimensional heavy-tailed time series which have finite $\alpha$-th moment with $\alpha \in (1,2]$. To handle the heavy-tailed dependent data, we propose a Catoni
Externí odkaz:
http://arxiv.org/abs/2411.05217
Autor:
Neumeyer, Natalie, Selk, Leonie
We consider linear models with scalar responses and covariates from a separable Hilbert space. The aim is to detect change points in the error distribution, based on sequential residual empirical distribution functions. Expansions for those estimated
Externí odkaz:
http://arxiv.org/abs/2411.04522
Autor:
Sandqvist, Oliver Lunding
This paper extends doubly robust censoring unbiased transformations to a broad class of censored data structures under the assumption of coarsening at random and positivity. This includes the classic survival and competing risks setting, but also enc
Externí odkaz:
http://arxiv.org/abs/2411.04909
Generalized linear mixed models (GLMMs) are a widely used tool in statistical analysis. The main bottleneck of many computational approaches lies in the inversion of the high dimensional precision matrices associated with the random effects. Such mat
Externí odkaz:
http://arxiv.org/abs/2411.04729
Autor:
Stepanova, Natalia, Turcicova, Marie
We observe an unknown regression function of $d$ variables $f(\boldsymbol{t})$, $\boldsymbol{t} \in[0,1]^d$, in the Gaussian white noise model of intensity $\varepsilon>0$. We assume that the function $f$ is regular and that it is a sum of $k$-variat
Externí odkaz:
http://arxiv.org/abs/2411.04320
A kernel density estimator for data on the polysphere $\mathbb{S}^{d_1}\times\cdots\times\mathbb{S}^{d_r}$, with $r,d_1,\ldots,d_r\geq 1$, is presented in this paper. We derive the main asymptotic properties of the estimator, including mean square er
Externí odkaz:
http://arxiv.org/abs/2411.04166