scholarly journals Statistical Study of the Performance of Recursive Bayesian Filters with Abnormal Observations from Range Sensors

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4159
Author(s):  
Manuel Castellano-Quero ◽  
Juan-Antonio Fernández-Madrigal ◽  
Alfonso-José García-Cerezo
Keyword(s):  
Mobile Robots ◽  
Statistical Methods ◽  
Statistical Approach ◽  
Statistical Study ◽  
Estimation Problem ◽  
Real Environment ◽  
Complete Treatment ◽  
The Impact ◽  
Range Sensors ◽  
Bayesian Filters

Range sensors are currently present in countless applications related to perception of the environment. In mobile robots, these devices constitute a key part of the sensory apparatus and enable essential operations, that are often addressed by applying methods grounded on probabilistic frameworks such as Bayesian filters. Unfortunately, modern mobile robots have to navigate within challenging environments from the perspective of their sensory devices, getting abnormal observations (e.g., biased, missing, etc.) that may compromise these operations. Although there exist previous contributions that either address filtering performance or identification of abnormal sensory observations, they do not provide a complete treatment of both problems at once. In this work we present a statistical approach that allows us to study and quantify the impact of abnormal observations from range sensors on the performance of Bayesian filters. For that, we formulate the estimation problem from a generic perspective (abstracting from concrete implementations), analyse the main limitations of common robotics range sensors, and define the factors that potentially affect the filtering performance. Rigorous statistical methods are then applied to a set of simulated experiments devised to reproduce a diversity of situations. The obtained results, which we also validate in a real environment, provide novel and relevant conclusions on the effect of abnormal range observations in these filters.

The Classical Theory of risk— a statistical approach

1948 ◽  
Vol 7 (03) ◽  
pp. 126-143
Author(s):  
Kennedy Williams
Keyword(s):  
Life Table ◽  
Statistical Methods ◽  
Frequency Distribution ◽  
Classical Theory ◽  
Statistical Approach ◽  
Statistical Study ◽  
Study Group ◽  
General Utility ◽  
Uniform Treatment

The purpose of this note is to develop some of the formulae of the classical theory of risk by a uniform treatment in which the “deaths’ column of the life table is considered as a discontinuous frequency distribution. The paper thus forms an example of the application of standard statistical processes to actuarial theory, and also supplies demonstrations of certain of the results quoted without proof in the survey by E. Lukacs. The aim has been to provide an elementary introduction both to an actuarial subject long neglected in this country, and to statistical methods of general utility.The paper owes its origin to a stimulating series of talks on the Theory of Risk, given by S. Vajda to the statistical Study Group of the Society. The particular approach adopted and the treatment of composite policies are thought to be original.

scholarly journals The Bayesian Approach to Audit Evidence: Quantifying Statistical Evidence using the Bayes Factor

2021 ◽  
Author(s):  
Koen Derks ◽  
jacques de swart ◽  
Eric-Jan Wagenmakers ◽  
ruud wetzels
Keyword(s):  
Bayesian Inference ◽  
Statistical Methods ◽  
Bayes Factor ◽  
Statistical Approach ◽  
Statistical Evidence ◽  
P Value ◽  
Audit Data ◽  
Alternative Approach ◽  
The Impact ◽  
Audit Standards

The impact of statistical methods on the audit practice is growing because of the increasing availability of audit data and the statistical methods to analyze these data. A key aspect in the statistical approach to auditing is assessing the strength of evidence for or against a hypothesis. Unfortunately, the often-used frequentist statistical methods cannot provide the statistical evidence that audit standards demand directly nor easily. In this article we discuss an alternative approach that can provide this evidence: Bayesian inference. Firstly, we explore the philosophical differences between frequentist and Bayesian inference. Secondly, we discuss misconceptions in the interpretation of frequentist statistical evidence, and finally we discuss how Bayesian inference allows the auditor to obtain and interpret statistical evidence in line with audit standards via its alternative to the p value, the Bayes factor.

Exploring the impact of introducing a physical model into statistical methods on the evaluation of regional scale debris flow susceptibility

2021 ◽  
Vol 106 (1) ◽  
pp. 881-912
Author(s):  
Jingbo Sun ◽  
Shengwu Qin ◽  
Shuangshuang Qiao ◽  
Yang Chen ◽  
Gang Su ◽  
...  
Keyword(s):  
Debris Flow ◽  
Physical Model ◽  
Statistical Methods ◽  
Regional Scale ◽  
The Impact ◽  
Debris Flow Susceptibility

scholarly journals Using multiple imputation to classify potential outcomes subgroups

2021 ◽  
pp. 096228022110028
Author(s):  
Yun Li ◽  
Irina Bondarenko ◽  
Michael R Elliott ◽  
Timothy P Hofer ◽  
Jeremy MG Taylor
Keyword(s):  
Multiple Imputation ◽  
Statistical Methods ◽  
The United States ◽  
Treatment Selection ◽  
Potential Outcomes ◽  
Model Framework ◽  
Medical Tests ◽  
Gene Assay ◽  
The Impact ◽  
Test Result

With medical tests becoming increasingly available, concerns about over-testing, over-treatment and health care cost dramatically increase. Hence, it is important to understand the influence of testing on treatment selection in general practice. Most statistical methods focus on average effects of testing on treatment decisions. However, this may be ill-advised, particularly for patient subgroups that tend not to benefit from such tests. Furthermore, missing data are common, representing large and often unaddressed threats to the validity of most statistical methods. Finally, it is often desirable to conduct analyses that can be interpreted causally. Using the Rubin Causal Model framework, we propose to classify patients into four potential outcomes subgroups, defined by whether or not a patient’s treatment selection is changed by the test result and by the direction of how the test result changes treatment selection. This subgroup classification naturally captures the differential influence of medical testing on treatment selections for different patients, which can suggest targets to improve the utilization of medical tests. We can then examine patient characteristics associated with patient potential outcomes subgroup memberships. We used multiple imputation methods to simultaneously impute the missing potential outcomes as well as regular missing values. This approach can also provide estimates of many traditional causal quantities of interest. We find that explicitly incorporating causal inference assumptions into the multiple imputation process can improve the precision for some causal estimates of interest. We also find that bias can occur when the potential outcomes conditional independence assumption is violated; sensitivity analyses are proposed to assess the impact of this violation. We applied the proposed methods to examine the influence of 21-gene assay, the most commonly used genomic test in the United States, on chemotherapy selection among breast cancer patients.

Measuring Entrepreneurial Self-efficacy: A Comprehensive Scale

2021 ◽  
pp. 239395752110196
Author(s):  
Neha Taneja Chawla ◽  
Hitesh Bhatia
Keyword(s):  
Impact Assessment ◽  
Statistical Methods ◽  
Self Efficacy ◽  
Reliability And Validity ◽  
Entrepreneurship Education ◽  
Education Programs ◽  
Entrepreneurial Behaviour ◽  
Indian Context ◽  
The World ◽  
The Impact

With the increasing popularity of entrepreneurship education programs across the world, the impact assessment of such programs has gathered considerable interest of the researchers. Growing number of studies are including entrepreneurial self-efficacy (ESE) as a key predictor of future entrepreneurial behaviour and hence the scale for measuring ESE is central to majority of studies pertaining to entrepreneurship education and entrepreneurial behaviour. This study attempts to refine the existing instruments for measuring ESE by extensively reviewing the notable scales of ESE in literature and develops a comprehensive scale of ESE relevant in the Indian context. The additional components are added to the existing scales through expert discussions with the academicians as well as entrepreneurs. The scale is further verified for its reliability and validity by using appropriate statistical methods.

Most Often Motivated by Social Media: The Who, the What, and the How Much—Experience from Poland

2021 ◽  
Vol 13 (20) ◽  
pp. 11193
Author(s):  
Karol Król ◽  
Dariusz Zdonek
Keyword(s):  
Social Media ◽  
Intrinsic Motivation ◽  
Statistical Methods ◽  
The Other ◽  
Public Expression ◽  
Other Hand ◽  
The Impact ◽  
The Way

Content published in social media (SM) can be motivating. It can induce action, stimulate demand, and shape opinions. On the other hand, it can demotivate, cause helplessness, or overwhelm with information. Still, the impact of SM is not always the same. The paper aims to analyse the relations between sex, personality, and the way social media is used and motivation to take specific actions. The conclusions are founded on a survey (n = 462). The data were analysed with statistical methods. The study revealed that the use of SM has a significant impact on the motivation to act. Browsing through descriptions and photographs of various achievements posted by others in SM increased the intrinsic motivation of the respondents. Positive comments and emojis had a similar effect. Moreover, women and extraverts noted a significantly greater impact of SM on their intrinsic motivation concerning health and beauty effort, travel, hobby, and public expression of opinions than men and introverts. The results can be useful to recruiters. Extravert women that are open to cooperation, thorough, and well-organised are more likely to be active in SM.

scholarly journals A Statistical Approach to Model the H-Index Based on the Total Number of Citations and the Duration from the Publishing of the First Article

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Mohammad Reza Mahmoudi ◽  
Marzieh Rahmati ◽  
Zulkefli Mansor ◽  
Amirhosein Mosavi ◽  
Shahab S. Band
Keyword(s):  
Nonlinear Regression ◽  
Research Funding ◽  
Statistical Approach ◽  
Practical Approach ◽  
H Index ◽  
Model Based ◽  
Funding Agencies ◽  
Number Of Citations ◽  
The Impact

The productivity of researchers and the impact of the work they do are a preoccupation of universities, research funding agencies, and sometimes even researchers themselves. The h-index (h) is the most popular of different metrics to measure these activities. This research deals with presenting a practical approach to model the h-index based on the total number of citations (NC) and the duration from the publishing of the first article (D1). To determine the effect of every factor (NC and D1) on h, we applied a set of simple nonlinear regression. The results indicated that both NC and D1 had a significant effect on h ( p  < 0.001). The determination of coefficient for these equations to estimate the h-index was 93.4% and 39.8%, respectively, which verified that the model based on NC had a better fit. Then, to record the simultaneous effects of NC and D1 on h, multiple nonlinear regression was applied. The results indicated that NC and D1 had a significant effect on h ( p  < 0.001). Also, the determination of coefficient for this equation to estimate h was 93.6%. Finally, to model and estimate the h-index, as a function of NC and D1, multiple nonlinear quartile regression was used. The goodness of the fitted model was also assessed.

scholarly journals Impact of Knowledge Management Infrastructure on Intellectual Capital

2018 ◽  
Vol 2 (2) ◽  
pp. 185-199
Author(s):  
Khaled Zaidan Abdul Hadi ◽  
Rawia Mohamed Wajih Jarges
Keyword(s):  
Knowledge Management ◽  
Statistical Methods ◽  
Intellectual Capital ◽  
Exploratory Study ◽  
Research Problem ◽  
Overall Performance ◽  
The Impact ◽  
Descriptive Method ◽  
Design And Construction

The research aims to demonstrate the impact of knowledge management infrastructure in intellectual capital through a exploratory study of the views of a sample of individuals in the Institute of Management / Rusafa. The interest in the knowledge management infrastructure contributes to increasing the effectiveness of the intellectual capital of the research sample. The research problem focused on the following questions: Is there a clear perception in the researched organization about the knowledge management infrastructure? Is there a clear perception in the researched organization about intellectual capital? What is the nature of the correlation and influence relationships between the knowledge management infrastructure and the intellectual capital? In order to answer the above questions, the analytical descriptive method was adopted through the design and construction of a scale that has the ability to measure the main dimensions of the research. The questionnaire (35) was distributed by means of an objective sample for a number of teachers as the research sample. In order to analyze the data, a set of statistical methods was used. The research found a significant correlation between the infrastructure of knowledge management and intellectual capital. A number of suggestions were made, including the need to pay attention to the knowledge management infrastructure, which would positively affect the intellectual capital of individuals and the overall performance of the researched organization.

scholarly journals Statistical study of the impact of climate warming on productivity

2020 ◽  
Vol 1515 ◽  
pp. 052071
Author(s):  
A P Zinchenko ◽  
O B Tarasova ◽  
N I Pyzhikova
Keyword(s):  
Climate Warming ◽  
Statistical Study ◽  
The Impact

scholarly journals Non-Specific Adsorption of Hydrocarbons on Microporous Surfaces: A Comprehensive Molecular-Statistical/Chromatographic Approach

1992 ◽  
Vol 9 (2) ◽  
pp. 54-71 ◽  
Author(s):  
E.V. Aksenenko ◽  
Yu. I. Tarasevich
Keyword(s):  
Statistical Methods ◽  
Computational Methods ◽  
Short Range ◽  
Statistical Approach ◽  
Adsorption Properties ◽  
Specific Adsorption ◽  
Thermodynamic Quantities ◽  
Good Correspondence ◽  
Symmetry Properties ◽  
Adsorption Systems

The results are presented of a series of investigations concerning the application of the molecular-statistical approach to the calculation of thermodynamic quantities for the adsorption of molecules in the Henry region on adsorbent surfaces possessing certain surface symmetry properties, and in particular for systems characterized by dispersion and polarization attraction and short-range atom-atom repulsion. Computational methods have been developed and the results for particular adsorption systems are presented with emphasis on the adsorption properties of layer silicates. Good correspondence between the calculated results and chromatographic data for a number of adsorbents strongly supports the view that the combination of chromatographic and molecular-statistical methods provides a powerful tool for the investigation of the structural and adsorption-selective characteristics of surface-porous adsorbents.

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