Robust projected principal component analysis for large-dimensional semiparametric factor modeling

Yang, Shuquan; Ling, Nengxiang

doi:10.1016/j.jmva.2023.105155

Cited by 5 publications

(1 citation statement)

References 33 publications

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“…The literature has extensively examined advanced methods of analysis. Several techniques can be employed to minimize data dimensionality, such as singular value decomposition (SVD) [4], principal component analysis (PCA) [5], and wavelet transformation [6].…”

Section: Biomedical Signal Analysismentioning

confidence: 99%

Interventions for Disrupted Sleep Patterns and Insomnia in Pediatric and Adolescent Populations Diagnosed with ASD

Beyers

2024

JBSHA

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The objective of this study is to develop a set of recommendations for effectively addressing sleep disturbance in adolescents and children with autism spectrum disorder (ASD). This will be achieved through a comprehensive evaluation of both pharmacological and non-pharmacological approaches utilised in the treatment of sleep disruptions in this specific population. Healthcare professionals who are providing care for adolescents and children with ASD and experiencing sleep disturbances should actively investigate potential underlying factors contributing to the disruption, such as medication usage or the presence of comorbid conditions. Subsequently, it is crucial for clinicians to address these identified causes in order to effectively manage the sleep disturbances. When managing sleep disturbance, it is advisable for clinicians to first suggest behavioural interventions, either independently or in combination with pharmacological or nutraceutical treatments, in order to facilitate improved sleep for children and their families. In cases where behavioural interventions prove ineffective and comorbid conditions and concurrent drug usage have been appropriately managed, healthcare professionals may contemplate the administration of melatonin, commencing with a conservative dosage. It is advisable to recommend melatonin of pharmaceutical grade if it is readily available for clinical use. It is incumbent upon healthcare professionals to engage in comprehensive discussions regarding the potential advantages and drawbacks associated with the utilisation of melatonin among paediatric patients, adolescents, and their guardians.

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Section: Biomedical Signal Analysismentioning

confidence: 99%

Interventions for Disrupted Sleep Patterns and Insomnia in Pediatric and Adolescent Populations Diagnosed with ASD

Beyers

2024

JBSHA

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Dynamic Return Scenario Generation Approach for Large-Scale Portfolio Optimisation Framework

Neděla,

Ortobelli Lozza,

Tichý

2024

Comput Econ

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In this paper, we propose a complex return scenario generation process that can be incorporated into portfolio selection problems. In particular, we assume that returns follow the ARMA–GARCH model with stable-distributed and skewed t-copula dependent residuals. Since the portfolio selection problem is large-scale, we apply the multifactor model with a parametric regression and a nonparametric regression approaches to reduce the complexity of the problem. To do this, the recently proposed trend-dependent correlation matrix is used to obtain the main factors of the asset dependency structure by applying principal component analysis (PCA). However, when a few main factors are assumed, the obtained residuals of the returns still explain a non-negligible part of the portfolio variability. Therefore, we propose the application of a novel approach involving a second PCA to the Pearson correlation to obtain additional factors of residual components leading to the refinement of the final prediction. Future return scenarios are predicted using Monte Carlo simulations. Finally, the impact of the proposed approaches on the portfolio selection problem is evaluated in an empirical analysis of the application of a classical mean–variance model to a dynamic dataset of stock returns from the US market. The results show that the proposed scenario generation approach with nonparametric regression outperforms the traditional approach for out-of-sample portfolios.

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A Comprehensive Review on Healthcare Data Analytics

Olson

2023

JBSHA

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Healthcare data can be collected from various sources, including sensors, and conventional electronic records, photographs, data from clinical notes/biological literature, among others. The variation in data representation and gathering gives rise to issues in both data interpretation and processing. The methodologies required to analyze these diverse sources of data exhibit considerable variation. The presence of heterogeneity within the data gives rise to a distinct set of challenges when it comes to the processes of integration and analysis. This article presents a detailed review of healthcare data analytics and the respective data sources. Secondly, it discusses advanced data analytics for the healthcare sector, and its practical systems as well as applications of healthcare data analytics.

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Robust projected principal component analysis for large-dimensional semiparametric factor modeling

Cited by 5 publications

References 33 publications

Interventions for Disrupted Sleep Patterns and Insomnia in Pediatric and Adolescent Populations Diagnosed with ASD

Interventions for Disrupted Sleep Patterns and Insomnia in Pediatric and Adolescent Populations Diagnosed with ASD

Dynamic Return Scenario Generation Approach for Large-Scale Portfolio Optimisation Framework

A Comprehensive Review on Healthcare Data Analytics

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