Spearman rank correlation of the bivariate Student t and scale mixtures of normal distributions

Heinen, Andréas; Valdesogo, Alfonso

doi:10.1016/j.jmva.2020.104650

Cited by 14 publications

(6 citation statements)

References 30 publications

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“…Extension of the results to the skew t (ST) distribution of Azzalini and Capitanio (2003) are not straightforward but are an interesting avenue for further research. As the ST is a scale mixture of the SN, the expressions might involve conditioning densities, such as those studied by Heinen and Valdesogo (2020) in the context of the Spearman's rank correlations of scale mixtures of normals. However, it is unclear how to leverage the results of this paper to deal with the case of the extended skew t (EST) of Arellano‐Valle and Genton (2010), and the unified multivariate skew‐

t

distribution recently studied in Galarza et al (2020), as they are not scale mixtures of their SN counterparts.…”

Section: Discussionmentioning

confidence: 99%

The Kendall and Spearman rank correlations of the bivariate skew normal distribution

Heinen

Valdesogo

2022

Scandinavian J Statistics

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We derive the Kendall and Spearman rank correlation coefficients of the bivariate skew normal (SN) distribution. For a given correlation parameter, we provide conditions on the shape parameters, under which the SN is more dependent than the normal in terms of each of the two-rank correlations. We further show how our results can be used for rank-based estimation procedures of the correlation parameter and the equal shape parameter of the SN, whose consistency and asymptotic normality we establish.

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t

distribution recently studied in Galarza et al (2020), as they are not scale mixtures of their SN counterparts.…”

Section: Discussionmentioning

confidence: 99%

The Kendall and Spearman rank correlations of the bivariate skew normal distribution

Heinen

Valdesogo

2022

Scandinavian J Statistics

Self Cite

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“…We use the Spearman correlation coefficient because it has less strict requirements on the data conditions as long as the observations of the 2 variables are paired rank ratings data, or rank data converted from continuous variable observation data. 56,57 The rank correlation coefficient is given by where is the Spearman rank relational coefficient, is the difference between and , and represent the position of the original data in a sorted sequence.…”

Section: Methodsmentioning

confidence: 99%

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confidence: 99%

Monitoring the Relationship between Social Network Status and Influenza Based on Social Media Data

Yan,

Shan,

Zhang

et al. 2023

Disaster med. public health prep.

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Background: This article aims to analyze the relationship between user characteristics on social networks and influenza. Methods: Three specific research questions are investigated: (1) we classify Weibo updates to recognize influenza-related information based on machine learning algorithms and propose a quantitative model for influenza susceptibility in social networks; (2) we adopt in-degree indicator from complex networks theory as social media status to verify its coefficient correlation with influenza susceptibility; (3) we also apply the LDA topic model to explore users’ physical condition from Weibo to further calculate its coefficient correlation with influenza susceptibility. From the perspective of social networking status, we analyze and extract influenza-related information from social media, with many advantages including efficiency, low cost, and real time. Results: We find a moderate negative correlation between the susceptibility of users to influenza and social network status, while there is a significant positive correlation between physical condition and susceptibility to influenza. Conclusions: Our findings reveal the laws behind the phenomenon of online disease transmission, and providing important evidence for analyzing, predicting, and preventing disease transmission. Also, this study provides theoretical and methodological underpinnings for further exploration and measurement of more factors associated with infection control and public health from social networks.

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“…or tap here to enter text. In the Spearman's rank order correlation, the closer the coefficient is to positive 1, the stronger the monotonic relationship [74]. A monotonic function is one that, when the value of its independent variable rises, never both grows and never lowers.…”

Section: Spearman's Rank Order Correlationmentioning

confidence: 99%

A Multivariate Analysis of the Variables Impacting the Level of BIM Expertise of Professionals in the Architecture, Engineering and Construction (AEC) Industries of the Developing World Using Nonparametric Tests

Takyi-Annan

Hong

2023

Buildings

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Building information modeling (BIM) mandates are becoming more widespread because BIM allows design and construction teams to operate more productively and also enables them to collect the data they generate during the process for use in operations and maintenance tasks. As a result, professionals in the architecture, engineering and construction (AEC) industries are expected to possess excellent BIM expertise. Despite the fact that the developing world has largely not adopted BIM, many studies have been conducted on BIM usage, awareness, drivers and barriers with a focus on the developing world. Numerous studies have pointed to the professionals’ lack of BIM expertise in the developing world’s AEC sector as a major barrier to BIM deployment. Nevertheless, no research has been conducted to assess the variables impacting the level of BIM expertise among professionals. After a detailed review of the literature, the study developed five study hypotheses and created a conceptual model to help assess the variables impacting the level of BIM expertise of professionals in the AEC industry in the developing world. After that, a questionnaire survey was carried out to collect data from 103 seasoned professionals in the Ghanaian construction industry. Nonparametric tests, such as the Kruskal–Wallis, pairwise post hoc Dunn, Mann–Whitney, Pearson’s correlation and the partial least squares structural equation modeling (PLS SEM) tests, were adopted to assess the relationships between the level of BIM expertise of professionals (BE) and the following variables: (1) profession (P), (2) the frequency of BIM use by professionals (BF), (3) the highest dimension of BIM adopted by AEC firms and companies (BD), (4) professionals’ perception of BIM (PB) and (5) the BIM implementation barriers (BIMIBs). P, BF, BD and PB were found to have a substantial impact on the level of BIM expertise acquired by professionals. With regards to professionals’ perception of the BIM software and process, only one (PB3–BIM is not useful to our company at the moment) out of ten of them was found to have a significant impact on BE, highlighting the impact of employers on the level of BIM expertise of professionals. In addition, the study discovered that any resolution made in an attempt to tackle the lack of/insufficient level of BIM expertise among professionals would prove futile without significant effort from the higher education sector (HES) of the developing world and the entire world at large. The study’s conceptual, empirical, managerial and theoretical implications and findings would serve as a roadmap for researchers, professionals and academics in developing nations as they endeavor to seek more ways of increasing BIM expertise among their professionals and to encourage BIM usage throughout the project lifecycle.

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Spearman rank correlation of the bivariate Student t and scale mixtures of normal distributions

Cited by 14 publications

References 30 publications

The Kendall and Spearman rank correlations of the bivariate skew normal distribution

The Kendall and Spearman rank correlations of the bivariate skew normal distribution

Monitoring the Relationship between Social Network Status and Influenza Based on Social Media Data

A Multivariate Analysis of the Variables Impacting the Level of BIM Expertise of Professionals in the Architecture, Engineering and Construction (AEC) Industries of the Developing World Using Nonparametric Tests

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