High-dimensional data bootstrap

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Web19 de mai. de 2024 · Abstract. This article reviews recent progress in high-dimensional bootstrap. We first review high-dimensional central limit theorems for distributions of … Web19 de fev. de 2024 · We propose a distributed bootstrap method for simultaneous inference on high-dimensional massive data that are stored and processed with many machines. The method produces a ℓ_∞-norm confidence region based on a communication-efficient de-biased lasso, and we propose an efficient cross-validation approach to tune the method …

Gaussian and bootstrap approximations for high-dimensional …

WebIn addition, we also show that the Gaussian-like convergence rates can be achieved for heavy-tailed data, which are less conservative than those obtained by the Bonferroni technique that ignores the dependency in the underlying data distribution. KW - Bootstrap. KW - Gaussian approximation. KW - High-dimensional inference. KW - U-statistics Web9 de out. de 2024 · This supports their use for practical analysis of high-dimensional data. 1.1 Related work and our contribution. Besides the growing literature in assessing uncertainty in high-dimensional statistical inference mentioned at the beginning of the introductory section, the use of the bootstrap has been advocated in other works. simply mac east cobb

Finding Cointegration Rank in High Dimensional Systems Using …

Web16 de mar. de 2024 · We first review high-dimensional central limit theorems for distributions of sample mean vectors over the rectangles, bootstrap consistency results in high … Web10 de mar. de 2024 · Download Citation High-Dimensional Data Bootstrap This article reviews recent progress in high-dimensional bootstrap. We first review high-dimensional central limit theorems for distributions ... WebWe have two real datasets for this study, one is for wheat, and another is maize data . Wheat lines were genotyped by Triticarte Pty. Ltd. (Canberra, Australia) using 1447 … simply mac hamilton place mall

High-Dimensional Data Bootstrap - ResearchGate

Adapting prediction error estimates for biased complexity

Webhelps the Gaussian and bootstrap approximations. In Section 4, we apply the proposed bootstrap method to a number of important high-dimensional problems, including the data-dependent tuning parameter selec-tion in the thresholded covariance matrix estimator and the simultaneous inference of the covariance and Kendall’s tau rank correlation ... simply mac financingWeb29 de nov. de 2024 · In a high dimensional set-up, most existing methods either are computationally infeasible, or suffer from highly distorted Type-I errors, or both. We propose an easy-to-implement bootstrap method for high-dimensional WN test and prove its consistency for a variety of test statistics. simply mac eastchase

"Webbootstrap on high-dimensional stationary time series. Factor modelling or low-rank representation can project high-dimensional data into low-dimensional subspace. … " - High-dimensional data bootstrap

High-dimensional data bootstrap

High-Dimensional Mediation Analysis: A New Method Applied to …

WebBootstrap approximations from a methodological point of view, theoretical accuracies in MANOVA tests, and model selection criteria are also presented. ... High-Dimensional Data Analysis with Low-Dimensional Models - John Wright … Web4 de jun. de 2014 · This article studies bootstrap inference for high dimensional weakly dependent time series in a general framework of approximately linear statistics. The …

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Web19 de fev. de 2024 · We propose a distributed bootstrap method for simultaneous inference on high-dimensional massive data that are stored and processed with many machines. … Webderive high-dimensional empirical and multiplier bootstrap theorems that allow us to approximate P(SY n ∈ A) for A ∈ Are, Asi(a,d),orAsp(s) using the data X1,...,Xn. In …

Web14 de abr. de 2024 · A high-dimensional mediation analysis of MS on birth weight was performed using placental DNAm data from the EDEN mother–child cohort. At an FDR level of 10% (5%), 32 (20) CpGs were identified as mediators of MS on birth weight ( Figure 4A , adjusted maximum begin superscript 2 end superscript max 2 lowercase italic p less than … WebWe have two real datasets for this study, one is for wheat, and another is maize data . Wheat lines were genotyped by Triticarte Pty. Ltd. (Canberra, Australia) using 1447 Diversity Array Technology. This data set includes 599 lines observed for trait grain yield (GY) for four mega environments.

Webhigh dimensional systems. By data based or "parametric bootstrap" Monte Carlo simulations, we mean simulations where the Data Generating Process (DGP) uses the parame-ter values obtained from an estimation using actual data. We base our simulations on estimated parameter values in order to ascertain that our results are empirically … Web10 de dez. de 2024 · We carry out a numerical study of the spinless modular bootstrap for conformal field theories with current algebra U(1)c × U(1)c, or equivalently the linear programming bound for sphere packing in 2c dimensions. We give a more detailed picture of the behavior for finite c than was previously available, and we extrapolate as c → ∞. Our …

WebWe first review high-dimensional central limit theorems for distributions of sample mean vectors over the rectangles, bootstrap consistency results in high dimensions, and key …

WebHigh-dimensional Factor Pricing Models Qiang Xia College of Mathematics and Informatics, South China Agricultural University and ... H0 Bootstrap data Size (%) 8.6 4.5 7.8 5.8 5.9 5.7 2.6 Ha Bootstrap data Power (%) 18.2 69.6 65.0 74.4 74.5 74.4 9.2 Window 2 … raytheon sales 2021Web11 de jan. de 2024 · Multiple method comparisons and synthesis; datasets 1 and 2. Covariate coefficients and selection stability were estimated for all models using a bootstrap methodology, except for the conventional ... raytheon salesWeb30 de set. de 2016 · Download a PDF of the paper titled Gaussian and bootstrap approximations for high-dimensional U-statistics and their applications, by Xiaohui Chen. ... A two-step Gaussian approximation procedure that does not impose structural assumptions on the data distribution is proposed. simply mac idaho falls idWeb1 de dez. de 2024 · A factor-based bootstrap procedure is constructed, which conducts AR-sieve bootstrap on the extracted low-dimensional common factor time series and then recovers the bootstrap samples for original data from the factor model. This paper proposes a new AR-sieve bootstrap approach on high-dimensional time series. The … raytheon sales 2022Web4 de jun. de 2014 · Abstract. We focus on the problem of conducting inference for high dimensional weakly dependent time series. Our results are motivated by the applications in modern high dimensional inference ... raytheon saleWeb19 de ago. de 2024 · σ ̂ x 1 j is the estimator of the standard deviation of the jth element of X 1. 18 As the smoking effect is negative, “decreasing” means that the detrimental effects of smoking become stronger with age.. 19 The motivation for focusing on first-time mothers is discussed in AHL. In effect, the restricted sample enables more credible identification of … simply mac fort wayneWebThe bootstrap is a tool that allows for efficient evaluation of prediction performance of statistical techniques without having to set aside data for validation. This is especially … simply mac inc