Search results for "Multivariate statistics"
showing 10 items of 290 documents
CLUSTERING INCOMPLETE SPECTRAL DATA WITH ROBUST METHODS
2018
Abstract. Missing value imputation is a common approach for preprocessing incomplete data sets. In case of data clustering, imputation methods may cause unexpected bias because they may change the underlying structure of the data. In order to avoid prior imputation of missing values the computational operations must be projected on the available data values. In this paper, we apply a robust nan-K-spatmed algorithm to the clustering problem on hyperspectral image data. Robust statistics, such as multivariate medians, are more insensitive to outliers than classical statistics relying on the Gaussian assumptions. They are, however, computationally more intractable due to the lack of closed-for…
Within-student variability in learning experiences, and teachers’ perceptions of students’ task-focus
2016
In order to advance models of educational processes (intraindividual, intensive longitudinal), we propose a model in which we specify state and trait constructs, and an intraindividual variability construct. In our ecological momentary assessment study, we investigated how trait-level and intraindividual variability of students’ learning experiences (intrinsic and extrinsic motivation, task difficulty, effort exertion, help-seeking and competence evaluations) converged with teacher-reported student task-focus. 285 primary school students’ (Years 5 and 6) completed the Learning Experience Questionnaire using handheld computers, on average 13.6 learning episodes during one week (SD = 4.6; Ran…
Preparation, Execution and Experience: A Multivariate Evaluation of ANS-SNS Patterns
1985
Aims to verify with multivariate methods how autonomic-somatic changes (composed by skin conductance, heart rate, pulse amplitude, respiration, blood volume and flexor, frontal and orbicutaris oris EMG-measures) from specific patterns according to event-related demands both during (or after) and before events when contentual and temporal knowledge allowing preparation is varied.
246 Survival of elderly patients with endometrial cancer – predicted by preoperative G-8 geriatric screening tool
2021
Introduction/Background* We evaluated the prognostic impact of various global health assessment tools in accordance to conventional prognostic factors in patients with endometrial cancer (EC) older than 60 years. Methodology G-8 geriatric screening tool (G-8 geriatric score), Lee Schonberg prognostic index (Lee-Index), Charlson Comorbidity Index (CCI) and American Society of Anesthesiologists (ASA-PS) – Physical Status System were retrospectively determined in a consecutive cohort of elderly patients with EC. Univariate and multivariate Cox regression analyses and Kaplan-Meier method were performed to determine the impact of the global health assessment tools on progression free survival (P…
A Multivariate Age-Structured Stochastic Model with Immunization Strategies to Describe Bronchiolitis Dynamics
2021
Bronchiolitis has a high morbidity in children under 2 years old. Respiratory syncytial virus (RSV) is the most common pathogen causing the disease. At present, there is only a costly humanized monoclonal RSV-specific antibody to prevent RSV. However, different immunization strategies are being developed. Hence, evaluation and comparison of their impact is important for policymakers. The analysis of the disease with a Bayesian stochastic compartmental model provided an improved and more natural description of its dynamics. However, the consideration of different age groups is still needed, since disease transmission greatly varies with age. In this work, we propose a multivariate age-struct…
Indirect chronology method employing rare earth elements to identify Sagunto Castle mortar construction periods
2017
A novel indirect chronology method has been developed to identify Sagunto Castle construction periods. The method is based on the use of inductively coupled plasma mass spectrometry (ICP-MS) to determine rare earth elements (REE) and other trace elements in mortars. Additionally, a no destructive geochemical analysis based on X-ray fluorescence (XRF) was employed for major elements determination. Collected chemical data were processed through Principal Component Analysis (PCA) to highlight any differences among the mortars belonging to different buildings and construction periods. The results show that PCA analysis permits to discriminate construction periods according to mortar sample REE …
Investigating Relationships Between Music, Emotions, Personality, and Music-Induced Movement
2013
Listening to music makes us to move in various ways. The characteristics of these movements can be affected by several aspects, such as individual factors, musical features, or the emotional content of the music. In a study in which we presented 60 individuals with 30 musical stimuli representing different genres of popular music and recorded their movement with an optical motion capture system, we found significant correlations 1) between musical characteristics and the exhibited movement, 2) between the perceived emotional content of the music and the movement, and 3) between personality traits of the dancers and the movement. However, such separate analyses are incapable of investigating…
Suite of Statistical Models Forecasting Latvian GDP
2014
Abstract We develop a suite of statistical models to forecast Latvian GDP. We employ various univariate and multivariate econometric techniques to obtain short-term GDP projections and to assess the performance of the models. We also comprise the information contained in components of GDP and obtain short-term GDP projections from disaggregated perspective. We run out-of-sample forecasting procedures to evaluate GDP projections and to assess forecasting accuracy of all individual statistical models. We conclude that factor and bridge models are among the best individually performing models in the suite. Forecasting accuracy obtained using disaggregated models of factor and bridge models is …
Modelling Systemic Cojumps with Hawkes Factor Models
2013
Instabilities in the price dynamics of a large number of financial assets are a clear sign of systemic events. By investigating a set of 20 high cap stocks traded at the Italian Stock Exchange, we find that there is a large number of high frequency cojumps. We show that the dynamics of these jumps is described neither by a multivariate Poisson nor by a multivariate Hawkes model. We introduce a Hawkes one factor model which is able to capture simultaneously the time clustering of jumps and the high synchronization of jumps across assets.
Univariate and multivariate properties of wind velocity time series
2009
We analyze the time series of hourly average wind speeds measured at 29 different stations located in Sicily, a region with a complex morphology. The investigation, performed from the univariate as well as the multivariate point of view, evidences that the statistical properties of wind at the single sites have features that are not reproduced by standard models and, thus, require specific modeling. Moreover, the synchronous evolution of wind velocity presents a cluster structure, obtained with different algorithms, that persists in the standard deviation too.