Nonparametric estimation of the multivariate Spearman's footrule: A further discussion

Pérez, Ana; Alaiz, Mercedes Prieto; Chamizo, Fernando; Liebscher, Eckhard; Úbeda-Flores, Manuel

doi:10.1016/j.fss.2023.02.010

Cited by 9 publications

(3 citation statements)

References 35 publications

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“…The Spearman correlation test was carried out between the parameters of vegetation density, soil physical properties, and field infiltration rate values through correlation coefficients and scatterplots in RStudio software. According to [21], this analysis was carried out to see the level of strength (closeness), the direction of the relationship, and the significance between parameters. The Spearman correlation coefficient is calculated using the following equation [35]: = amount of data The Spearman correlation test was chosen to make the resulting coefficient more accurate because the repeat data used was less than 30 samples [22].…”

Section: Spearman Correlation Testmentioning

confidence: 99%

Assesing Infiltration Rate and Soil Physical Properties at Different Vegetation Densities in the Jasinga Silviculture Teaching Industry (JSTI) Area

Rusdiana,

Rizki,

Winata

2024

IOP Conf. Ser.: Earth Environ. Sci.

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The Jasinga Silviculture Teaching Industry (JSTI) area is a research forest with ecosystem conditions that have yet to be widely known. Research on the local ecosystem is needed, especially regarding vegetation, soil, and the hydrological cycle. Vegetation densities in the JSTI area are uneven, which affects groundwater absorption (infiltration rate). This study aimed to identify the infiltration rate and soil physical properties at different vegetation densities. The research plot was determined through purposive sampling techniques based on the level of vegetation density. The research methods carried out were analysis of vegetation density and composition, identification of soil physical properties (such as organic matter content, bulk density, porosity, and moisture content), measuring field infiltration rates using a double-ring infiltrometer, and analyzed the Spearman correlation. The results showed that dense vegetation has the highest score of organic matter content (> 4%), the bulk density is moderate, the porous category dominates the porosity, and the water content and infiltration rate were greater than sparse vegetation plots. Therefore, it is recommended to carry out planting activities at sparse vegetation density in the JSTI area.

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Section: Spearman Correlation Testmentioning

confidence: 99%

Assesing Infiltration Rate and Soil Physical Properties at Different Vegetation Densities in the Jasinga Silviculture Teaching Industry (JSTI) Area

Rusdiana,

Rizki,

Winata

2024

IOP Conf. Ser.: Earth Environ. Sci.

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“…Example 7. For all t ∈ [0, +∞], given the generators ϕ 1 (t) = 1−δ e t −δ , with δ ∈ [0, 1], and ϕ 2 (t) = (1 + γt) −1/γ , with γ > 0, we consider the generalizations to n-dimensions of the AMH family of Archimedean two-copulas-denoted by C AMH n,ϕ 1 ,δ -given in Example 5 (see [31]) and a Clayton subfamily of Archimedean two-copulas-denoted by C C n,ϕ 2 ,γ -(see [31,32]). For the sake of simplicity, we consider γ = 1.…”

Section: The Pd(−1) Order For Archimedean N-copulasmentioning

confidence: 99%

Directional Dependence Orders of Random Vectors

de Amo,

Rodríguez-Griñolo,

Úbeda-Flores

2024

Mathematics

Self Cite

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“…Because each indicator has a different level of influence, this study uses the PCA method [40,41] and the Spearman algorithm [42] to select the features of complex parameters and screen out the important parameters that have the greatest impact on the amount of unconventional water use in Harbin. Principal component analysis (PCA) is a widely used data dimensionality reduction algorithm that determines the significant influence of the correlation coefficient of the factors.…”

Section: Identifying Key Indicatorsmentioning

confidence: 99%

Unconventional Water Use Allocation in Harbin, China

Guo,

Sun,

Teng

et al. 2023

Water

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To lessen the strain on Harbin’s water resources and enhance the environment, it is crucial to analyze the key determining factors for the use of unconventional water resources in the city and to allocate unconventional water reasonably among various industries in the planning year. In this study, a back-propagation neural network (BP neural network) model is used to predict the potential for unconventional water resource utilization in the planning year (2025), a gray correlation analysis model is used to evaluate water-using industries, and finally, an unconventional water resource allocation scheme for the study is used to determine the main influencing factors and determine the weights of key indicators. The findings demonstrate a strong correlation between Harbin’s level of investment and construction, economic efficiency, cost, level of water demand, and social factors, as well as a low level of utilization of unconventional water resources throughout the city.

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Nonparametric estimation of the multivariate Spearman's footrule: A further discussion

Cited by 9 publications

References 35 publications

Assesing Infiltration Rate and Soil Physical Properties at Different Vegetation Densities in the Jasinga Silviculture Teaching Industry (JSTI) Area

Assesing Infiltration Rate and Soil Physical Properties at Different Vegetation Densities in the Jasinga Silviculture Teaching Industry (JSTI) Area

Directional Dependence Orders of Random Vectors

Unconventional Water Use Allocation in Harbin, China

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