نتایج جستجو برای: dimensional error

تعداد نتایج: 639885  

Journal: :آب و خاک 0
مهدی پناهی سید مجید میرلطیفی فریبرز عباسی

abstract this study addresses two dimensional infiltration from irrigated furrows. the basic approach is to develop a two-dimensional infiltration as a combination of the corresponding one-dimensional vertical and an edge effect. the edge effect is the difference between the cumulative infiltration per unit of adjusted wetting perimeter and the corresponding one-dimensional infiltration. this a...

Journal: :international journal of industrial mathematics 2014
n. mikaeilvand s. noeiaghdam

‎the subject of this paper is the solution of the fredholm integral equation with toeplitz, hankel and the toeplitz plus hankel kernel. the mean value theorem for integrals is applied and then extended for solving high dimensional problems and finally, some example and graph of error function are presented to show the ability and simplicity of the ‎method.

Journal: :The Journal of Korean Institute of Communications and Information Sciences 2014

Journal: :Journal of Multivariate Analysis 2021

For a high dimensional linear model with finite number of covariates measured errors, we study statistical inference on the parameters associated error-prone covariates, and propose new corrected decorrelated score test corresponding type estimator. This work was motivated by real data example, where both low phenotypic variables genotypic variables, single nucleotide polymorphisms (SNPs), are ...

2007
Il-Pyung Park John R. Kender

In this paper we describe error detection and error recovery methods applicable to large scale unstructured environmental navigation. We relax our prior assumption of error-free following of topological landmarks; the navigator is “permitted” to make mistakes during its journey. The error detection method involves the navigator observing its immediate environmental surroundings, and checking fo...

Journal: :Mathematics 2023

High-dimensional measurement error data are becoming more prevalent across various fields. Research on regression models has gained momentum due to the risk of drawing inaccurate conclusions if errors ignored. When dimension p is larger than sample size n, it challenging develop statistical inference methods for high-dimensional existence bias, nonconvexity objective function, high computationa...

Journal: :Journal of the American Statistical Association 2017

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