SAPI: Statistical Analysis of Propagation of Incidents. A new approach for rescheduling trains after disruptions

2011 ◽  
Vol 215 (1) ◽  
pp. 227-243 ◽  
Author(s):  
Rodrigo Acuna-Agost ◽  
Philippe Michelon ◽  
Dominique Feillet ◽  
Serigne Gueye
Keyword(s):  
Statistical Analysis ◽  
New Approach

Recent and Planned Developments of the Program OxCal

Radiocarbon ◽  
2013 ◽  
Vol 55 (2) ◽  
pp. 720-730 ◽  
Author(s):  
Christopher Bronk Ramsey ◽  
Sharen Lee
Keyword(s):  
Statistical Analysis ◽  
Statistical Methods ◽  
Software Package ◽  
Model Averaging ◽  
Data Sets ◽  
Radiocarbon Dates ◽  
New Approach ◽  
New Models ◽  
Multiphase Models ◽  
Deposition Models

OxCal is a widely used software package for the calibration of radiocarbon dates and the statistical analysis of 14C and other chronological information. The program aims to make statistical methods easily available to researchers and students working in a range of different disciplines. This paper will look at the recent and planned developments of the package. The recent additions to the statistical methods are primarily aimed at providing more robust models, in particular through model averaging for deposition models and through different multiphase models. The paper will look at how these new models have been implemented and explore the implications for researchers who might benefit from their use. In addition, a new approach to the evaluation of marine reservoir offsets will be presented. As the quantity and complexity of chronological data increase, it is also important to have efficient methods for the visualization of such extensive data sets and methods for the presentation of spatial and geographical data embedded within planned future versions of OxCal will also be discussed.

LAMDA-HAD, an Extension to the LAMDA Classifier in the Context of Supervised Learning

2020 ◽  
Vol 19 (01) ◽  
pp. 283-316 ◽  
Author(s):  
Luis Morales ◽  
José Aguilar ◽  
Danilo Chávez ◽  
Claudia Isaza
Keyword(s):  
Data Analysis ◽  
Statistical Analysis ◽  
Unsupervised Learning ◽  
Supervised Learning ◽  
Learning Algorithm ◽  
New Approach ◽  
Supervised And Unsupervised Learning ◽  
Training Stage

This paper proposes a new approach to improve the performance of Learning Algorithm for Multivariable Data Analysis (LAMDA). This algorithm can be used for supervised and unsupervised learning, based on the calculation of the Global Adequacy Degree (GAD) of one individual to a class, through the contributions of all its descriptors. LAMDA has the capability of creating new classes after the training stage. If an individual does not have enough similarity to the preexisting classes, it is evaluated with respect to a threshold called the Non-Informative Class (NIC), this being the novelty of the algorithm. However, LAMDA has problems making good classifications, either because the NIC is constant for all classes, or because the GAD calculation is unreliable. In this work, its efficiency is improved by two strategies, the first one, by the calculation of adaptable NICs for each class, which prevents that correctly classified individuals create new classes; and the second one, by computing the Higher Adequacy Degree (HAD), which grants more robustness to the algorithm. LAMDA-HAD is validated by applying it in different benchmarks and comparing it with LAMDA and other classifiers, through a statistical analysis to determinate the cases in which our algorithm presents a better performance.

scholarly journals New approach to the retrieval of AOD and its uncertainty from MISR observations over dark water

2018 ◽  
Vol 11 (1) ◽  
pp. 429-439 ◽  
Author(s):  
Marcin L. Witek ◽  
Michael J. Garay ◽  
David J. Diner ◽  
Michael A. Bull ◽  
Felix C. Seidel
Keyword(s):  
Statistical Analysis ◽  
Cost Function ◽  
Entire Range ◽  
Cost Functions ◽  
Retrieval Algorithm ◽  
New Approach ◽  
Aerosol Retrieval ◽  
Operational Algorithm ◽  
Confidence Index ◽  
The Cost

Abstract. A new method for retrieving aerosol optical depth (AOD) and its uncertainty from Multi-angle Imaging SpectroRadiometer (MISR) observations over dark water is outlined. MISR's aerosol retrieval algorithm calculates cost functions between observed and pre-simulated radiances for a range of AODs (from 0.0 to 3.0) and a prescribed set of aerosol mixtures. The previous version 22 (V22) operational algorithm considered only the AOD that minimized the cost function for each aerosol mixture and then used a combination of these values to compute the final, “best estimate” AOD and associated uncertainty. The new approach considers the entire range of cost functions associated with each aerosol mixture. The uncertainty of the reported AOD depends on a combination of (a) the absolute values of the cost functions for each aerosol mixture, (b) the widths of the cost function distributions as a function of AOD, and (c) the spread of the cost function distributions among the ensemble of mixtures. A key benefit of the new approach is that, unlike the V22 algorithm, it does not rely on empirical thresholds imposed on the cost function to determine the success or failure of a particular mixture. Furthermore, a new aerosol retrieval confidence index (ARCI) is established that can be used to screen high-AOD retrieval blunders caused by cloud contamination or other factors. Requiring ARCI ≥0.15 as a condition for retrieval success is supported through statistical analysis and outperforms the thresholds used in the V22 algorithm. The described changes to the MISR dark water algorithm will become operational in the new MISR aerosol product (V23), planned for release in 2017.

New approach to the probabilistic-statistical analysis of turbulent transport processes in plasma

2002 ◽  
Vol 28 (2) ◽  
pp. 111-124 ◽  
Author(s):  
G. M. Batanov ◽  
V. E. Bening ◽  
V. Yu. Korolev ◽  
A. E. Petrov ◽  
K. A. Sarksyan ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Turbulent Transport ◽  
Transport Processes ◽  
New Approach

Statistical Analysis of Forming Processes as a First Step in a Process-Chain Analysis: Novel PRO-CHAIN Components

2012 ◽  
Vol 504-506 ◽  
pp. 631-636 ◽  
Author(s):  
Daniela Steffes-Lai ◽  
Tanja Clees
Keyword(s):  
Statistical Analysis ◽  
Statistical Information ◽  
Process Chain ◽  
Parameter Sensitivity Analysis ◽  
Forming Process ◽  
Process Step ◽  
New Approach ◽  
Chain Analysis ◽  
Process Chains ◽  
Metal Blank

This paper presents a new approach for statistical analysis of process chains, including a parameter sensitivity analysis of each process step as a basis for dimension reduction, and an efficient interpolatory metamodel in order to predict new designs. A Monte Carlo alike evaluation of this metamodel results in the requested statistical information, e.g. quantiles of the output functionals. Numerical results are presented for the forming process of a ZStE340 metal blank of a B-pillar. Additionally, a brief overview of results of the process chain forming to crash is given.

scholarly journals Rethinking suicide: From pre-Durkheim suicidology to contemporary theories

2021 ◽  
Author(s):  
Hong-Kong T. Nguyen
Keyword(s):  
Information Processing ◽  
Statistical Analysis ◽  
18Th Century ◽  
New Approach

This essay reviews the research on suicide from the pre-Durkheim period in the 18th century to modern day. It highlights major developments in suicidology--the study of suicide--and suggests a new proposal. The new approach, built on the mindsponge model, integrates existing theories as well as Bayesian statistical analysis to facilitate our understanding of suicide through the lens of information processing and updating.

scholarly journals A New Approach to the Statistical Analysis of Non-Central Complex Gaussian Quadratic Forms With Applications

2019 ◽  
Vol 68 (7) ◽  
pp. 6734-6746 ◽  
Author(s):  
Pablo Ramirez-Espinosa ◽  
Laureano Moreno-Pozas ◽  
Jose F. Paris ◽  
Jose A. Cortes ◽  
Eduardo Martos-Naya
Keyword(s):  
Statistical Analysis ◽  
Quadratic Forms ◽  
Central Complex ◽  
New Approach
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