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检索条件"主题词=Statistical algorithms"

共 42 条记录，以下是31-40 订阅

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Wavelet Methods for Very-short Term Forecasting of Functional Time Series

Wavelet Methods for Very-short Term Forecasting of Functiona...

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作者： Nystrom, J. K AIR FORCE INSTITUTE OF TECHNOLOGY WRIGHT-PATTERSON AFB OH GRADUATE SCHOOL OF ENGINEERING AND MANAGEMENT AIR FORCE INSTITUTE OF TECHNOLOGY WRIGHT-PATTERSON AFB OH

Space launch operations at Kennedy Space Center and Cape Canaveral Space Force Station (KSC/CCSFS) are complicated by unique requirements for near-real time determination of risk from lightning. Lightning forecast weather sensor networks produce data that are noisy, high volume, and high frequency time series for which traditional forecasting methods are often ill-suited. Current approaches result in significant residual uncertainties and consequentially may result in forecasting operational policies that are excessively conservative or inefficient. This work proposes a new methodology of wavelet-enabled semiparametric modeling to develop accurate and timely forecasts robust against chaotic functional data. Wavelets methods are first used to de-noise the weather data, which is then used to estimate a single-index model for forecasting. This semiparametric technique mitigates noise of the chaotic signal while avoiding any possible distributional misspecification.

关键词： Computational science Information science Neural networks Data mining Dimensionality reduction Experimental design Data science Knowledge management Surveys Machine learning statistical algorithms Supervised machine learning Detectors Information processing Sensor networks Air force Electromagnetic fields

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A Bayesian Approach to Multiple-Output Quantile Regression

A Bayesian Approach to Multiple-Output Quantile Regression

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作者： Guggisberg, Michael

This paper presents a Bayesian approach to multiple-output quantile regression. The unconditional model is proven to be consistent and asymptotically correct frequentist confidence intervals can be obtained. The prior for the unconditional model can be elicited as the ex-ante knowledge of the distance of the x1Ctau-Tukey depth contour to the Tukey median, the first prior of its kind. A proposal for conditional regression is also presented. The model is applied to the Tennessee Project Steps to Achieving Resilience STAR experiment and it finds a joint increase in x1C tau-quantile subpopulations for mathematics and reading scores given a decrease in the number of students per teacher. This result is consistent with, and much stronger than, the result one would find with multiple-output linear regression. Multiple-output linear regression finds the average mathematics and reading scores increase given a decrease in the number of students per teacher. However, there could still be subpopulations where the score declines. The multiple-output quantile regression approach confirms there are no quantile subpopulations of the inspected subpopulations where the score de-clines. This is truly a statement of no child left behind opposed to no average child left behind.

关键词： monte carlo method bayesian networks computational science random variables surveys information science operations research probability statistical algorithms data science databases probability distributions algorithms computations estimators statistics applied mathematics data analysis data mining mathematics

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A Tutorial on Bayesian Estimation and Tracking Techniques Applicable to Nonlinear and Non-Gaussian Processes

A Tutorial on Bayesian Estimation and Tracking Techniques Ap...

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作者： Haug, A. J.

Nonlinear filtering is the process of estimating and tracking the state of a nonlinearstochastic system from non-Gaussian noisy observation data. In this technical memorandum,we present an overview of techniques for nonlinear filtering for a wide varietyof conditions on the nonlinearities and on the noise. We begin with the developmentof a general Bayesian approach to filtering which is applicable to all linear or nonlinearstochastic systems. We show how Bayesian filtering requires integration over probabilitydensity functions that cannot be accomplished in closed form for the general nonlinear,non-Gaussian multivariate system, so approximations are required.

关键词： computational science kalman filters bayesian networks monte carlo method random variables mathematical filters gaussian distributions signal processing coordinate systems information science probability data science electrical engineering probability distributions statistical algorithms target tracking computational fluid dynamics distribution functions gaussian processes information processing

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Improving the Fairness of Coast Guard Recruitment and Selection with the ASVAB and AFCT: A Dynamic Measurement Modeling Paradigm

Improving the Fairness of Coast Guard Recruitment and Sele...

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作者： Dumas, D McNeish, D Dong, Y Duelberg, D OPM/USA Learning Center Center for Leadership development Washington DC OFFICE OF THE UNDER SECRETARY OF DEFENSE (PERSONNEL AND READINESS) WASHINGTON DC

A large-scale re-analysis of scores from the Armed Service Vocational Aptitude Battery/Armed Forces Classification Test (ASVAB/AFCT), the primary tools for military recruit accession and training qualification for occupational classification, was conducted using training data from the United States Coast Guard (USCG). The analysis evaluated whether these instruments could be used differently to increase the aperture for different candidate pools, including Underrepresented Minorities (URMs), for qualification into the Coast Guard, as well as qualification for a specific rate qualification. The idea to measure a recruit s learning capacity, by calculating the growth trajectories from in-between test scores, provides the military with more relevant information regarding trainability, which is a new and necessary focus for todays military due to advanced technical training requirements. The research found 10% of Coast Guard recruits re-take the ASVAB/AFCT in order to elevate composite scores, probably with the hopes of qualifying for their occupation of choice.

关键词： Propensity score matching Minority groups Information science Data science Data mining Psychology Students Surveys Coast guard Demography Educational psychology Knowledge management Probability statistical algorithms Statistics Applied psychology Behavioral research

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Study of Naval Wholesale Inventory Optimization Model

Study of Naval Wholesale Inventory Optimization Model

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作者： Hague, A Naval Postgraduate School Monterey CA

Navy Supply Systems Command manages a vast inventory of items to meet the fleets requirements. A requisition decision for restocking an item is made, in part, based on the planned minimum safety stock (PMSS) level. The Wholesale Inventory Optimization Model with Enterprise Resource Planning (WIOM-ERP) simulates the fleets requirement demand based on historic data to establish metrics that serve as the basis to recommend the PMSS levels. NAVSUP uses WIOM-ERP to balance its inventory between procurement persistence (avoidance of "churn") and fulfillment of demand (fill rate). WIOM-ERP provides the flexibility for planners to weigh the importance of each metric and shift the balance between churn and fill rate. Decision makers seek insight into the relative tradeoff between churn and fill rate, resulting from changing the weight of each metric. This study applies a high-dimensional statistical design of experiments to simulate different combinations of metric weights for the WIOM-ERP user inputs. The output of WIOM-ERP is recorded for each design point to calculate measures of performance (MOPs) for churn and fill rate. The data are analyzed by developing statistical metamodels for each MOP to determine the impact on the metrics of the factors, their interactions, and the resulting tradeoffs between different combinations of weights.

关键词： Databases Department of defense Ruby programming language Supply chain Experimental design Information science Operations research statistical algorithms Data science Regression analysis Simulations United states B band Blood coagulation factors C band California D band Factor analysis Literature surveys Mathematical programming

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Monte Carlo Simulation with Censored Sampling

Monte Carlo Simulation with Censored Sampling

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作者： Akin, E. W Naval Postgraduate School Monterey CA

We consider Monte Carlo simulation in a setting where the samples are subject to random censoring. Such censoring occurs in settings as varied and diverse as perimeter protection, survival analysis, and electro-magnetic spectrum monitoring. We introduce and analyze two estimators: one based on empirical likelihood methods and another rooted in control variates ideas. We show that the proposed estimators can dramatically reduce the estimator variance in relation to the crude Monte Carlo estimator while not sacrificing computational speed.

关键词： Information science Monte carlo method statistical algorithms Data science Maximum likelihood estimation Random variables Surveys Data mining Knowledge management Operations research Probability distributions statistical inference algorithms Estimators Numerical analysis Probability Sampling Statistics Theorems Computational complexity

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Artificial Intelligence Exploration (AIE) DARPA-PA-18-02-02 Artificial Intelligence Research Associate (AIRA)

Artificial Intelligence Exploration (AIE) DARPA-PA-18-02-02 ...

引用

作者： Garikipati, Krishna

We propose a Bayesian framework to develop new machine learning and operator inference methods to aid the discovery of physical phenomena and the prediction of material properties and responses. We specifically target the challenges in material physics associated with systematic attempts to a abstract complexity from a hierarchy of scales into predictive model forms and b delineate mechanisms of coupled materials physics. Our project develops the following tasks that unite artificial intelligence AI with the discovery of emergent physics I Scale bridging from quantum mechanics to continuum PDEs. 2 Physics discovery via system identification and operator inference. 3 Bayesian inference and uncertainty quantification for learning from data and quantifying predictive quality. 4 Optimal experimental design for intelligent data acquisition and management to achieve efficient high-level learning. The first two tasks address important application-specific problems and the next two tasks provide the AI interface.

关键词： neural networks computational science bayesian networks kalman filters information science machine learning information processing mathematical filters monte carlo method mechanics artificial intelligence artificial intelligence software bayesian inference data science statistical algorithms experimental design information systems materials acquisition algorithms

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Tutorial: Parametric Reliability Models

Tutorial: Parametric Reliability Models

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作者： Pinelis, Y. K Whitledge, W. R INSTITUTE FOR DEFENSE ANALYSES ALEXANDRIA VA OFFICE OF THE SECRETARY OF DEFENSE WASHINGTON DC OPERATIONAL TEST AND EVALUATION OFFICE OF THE SECRETARY OF DEFENSE WASHINGTON DC

This tutorial demonstrates how to plot reliability functions parametrically in R using the output from any reliability modeling software. It provides code and sample plots of reliability and failure rate functions with confidence intervals for three different skewed probability distributions: the exponential, the two-parameter Weibull, and the lognormal. These three distributions are the most common parametric models for reliability or survival analysis. This paper also provides mathematical background for the models and recommendations for when to use them.

关键词： Test and evaluation Probability distributions Confidence limits Data analysis Probability United states Information science Normal distribution Random variables Reliability statistical inference Covariance Data science Data sets High resolution Maximum likelihood estimation statistical algorithms Boundaries Distribution functions Equations

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Quantum Computing algorithms For Decision Making Under Uncertainty

Quantum Computing Algorithms For Decision Making Under Uncer...

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作者： Horesh, L Clarkson, K Kalantzis, V Squillante, M Ubaru, S Abboud, A IBM Yorktown Heights NY Air Force Research Laboratory - Information Directorate Rome NY Air Force Research Laboratory Rome NY Information Directorate

The Quantum Computing algorithms fundamental research project focuses on the challenge of design of quantum computing algorithms viable for near-term noisy quantum systems. An emphasis was set on design of algorithms that avoid taking unrealistic assumptions while offering theoretical rigor regarding the expected computational advantage. The activity addressed three major development initiatives, namely: algorithmic design, implementation and testing, quantum computing application scoping, and data porting.

关键词： Quantum computing Computational science Quantum information Air force Machine learning Information science Quantum computers Quantum properties Data mining Information processing statistical algorithms Trees (data structures) Artificial intelligence Computational complexity Data analysis Monte carlo method Probability distributions

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Impact of Behavioral and Psychosocial Protective Factors on Health Outcomes in Heart Failure Patients: A Structural Equation Model Analysis

Impact of Behavioral and Psychosocial Protective Factors on ...

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作者： Garza, J. A UNIFORMED SERVICES UNIV OF THE HEALTH SCIENCES BETHESDA MD

Objective: Heart failure (HF) rates have continued to increase, despite decreases in the incidence of heart disease. In addition to health consequences of HF, it contributes a staggering financial cost to the individual, caregiver, and the broader health care. One significant component of the total cost and burden is frequent hospitalizations. HF research has suggested the importance of behavioral and psychological risk factors, but there has also been increased examination of protective factors that may reduce the progression of HF and improve overall prognosis. This study aims to determine if psychosocial or behavioral protective factors predict improved long-term health status and decreased hospitalizations in HF patients. The present study used a Structural Equation Model (SEM) approach to examine the impact of protective factors on outcomes in HF patients. Method and Results: This study is based on previously collected data from the Behavioral Triggers of Heart Failure (BETRHEART) study. One hundred and fifty participants were administered self-report measures on psychosocial (e.g., positive affect, optimism, self-efficacy, social support, coping styles), and behavioral variables (e.g., medication adherence, sleep quality, physical activity, adherence to a healthy diet), at the baseline assessment and up to a total of 39 months. The Kansas City Cardiomyopathy Questionnaire (KCCQ) was also administered at the baseline and subsequent follow-up assessments to evaluate HF symptoms and health status. Data on hospitalizations were collected over the entire 39-month study period. SEM was conducted to determine whether the two theoretical factors Psychosocial Protective Factor and Behavioral Protective Factor predict hospitalizations and KCCQ health status at a 9-month and up to a 39-month follow-up. Results of a confirmatory factor analysis indicated some of the items/measures had low factor loadings and were removed based on model fit statistics.

关键词： Health services Medical personnel Families (human) Data analysis Surveys Information science Heart diseases Regression analysis Cardiovascular diseases Data science Social psychology statistical algorithms Data mining Factor analysis Heart failure Cardiomyopathies Knowledge management

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