Search results for "Additive model"
showing 10 items of 28 documents
Functional principal component analysis for multivariate multidimensional environmental data
2015
Data with spatio-temporal structure can arise in many contexts, therefore a considerable interest in modelling these data has been generated, but the complexity of spatio-temporal models, together with the size of the dataset, results in a challenging task. The modelization is even more complex in presence of multivariate data. Since some modelling problems are more natural to think through in functional terms, even if only a finite number of observations is available, treating the data as functional can be useful (Berrendero et al. in Comput Stat Data Anal 55:2619–2634, 2011). Although in Ramsay and Silverman (Functional data analysis, 2nd edn. Springer, New York, 2005) the case of multiva…
Bending Work Time: Curvilinear Relationship Between Working Time Dimensions and Psychological and Somatic Symptoms.
2020
Objectives Study examines the curvilinear associations of working time dimensions (working hours, time pressure, work schedules, and control of work time and pace) on psychological and somatic symptoms. Methods Representative Finnish Quality-of-Work-Life Surveys conducted in 2003, 2008 and 2013 were restricted to those (N=11,165) regularly working over 10h/week with more than one-year tenure in their job. Generalised additive models were utilised in analysis. Results Working hours had U-shaped relationships with psychosomatic symptoms, while time pressure had a threshold effect. Work pace control had linear effect. The effects of work time control and work schedules were insignificant. Ther…
Assessing the performance of GIS- based machine learning models with different accuracy measures for determining susceptibility to gully erosion
2019
Assessing the performance of GIS- based machine learning models withdifferent accuracy measures for determining susceptibility togully erosionYounes Garosia, Mohsen Sheklabadia,⁎, Christian Conoscentib, Hamid Reza Pourghasemic,d, Kristof Van Ooste,faFaculty of Agriculture, Department of Soil Science, Bu Ali Sina University, Ahmadi Roshan Avenue, 6517838695 Hamedan, IranbDepartment of Earth and Sea Sciences (DISTEM), University of Palermo, Via Archirafi22, 90123 Palermo, ItalycCollege of Marine Sciences and Engineering, Nanjing Normal University, Nanjing, 210023, ChinadDepartment of Natural Resources and Environmental Engineering, College of Agriculture, Shiraz University, Shiraz, IraneA- Fo…
Quantifying unpredictability: A multiple-model approach based on satellite imagery data from Mediterranean ponds.
2017
Fluctuations in environmental parameters are increasingly being recognized as essential features of any habitat. The quantification of whether environmental fluctuations are prevalently predictable or unpredictable is remarkably relevant to understanding the evolutionary responses of organisms. However, when characterizing the relevant features of natural habitats, ecologists typically face two problems: (1) gathering long-term data and (2) handling the hard-won data. This paper takes advantage of the free access to long-term recordings of remote sensing data (27 years, Landsat TM/ETM+) to assess a set of environmental models for estimating environmental predictability. The case study inclu…
Semiparametric stochastic frontier models: A generalized additive model approach
2017
Abstract The choice of the functional form of the frontier into a stochastic frontier model is typically neglected in applications and canonical functions are usually considered. This paper introduces a semiparametric approach for stochastic frontier estimation that extends previous works based on pseudo-likelihood estimators allowing flexibility in model selection and capability of imposing monotonicity and concavity constraints. For these purposes the present work introduces a generalized additive framework that moreover permits to model the influence of contextual/environmental factors to the hypothesized production process by the relative extension given by generalized additive models f…
Predictive distribution models of European hake in the south-central Mediterranean Sea
2017
The effective management and conservation of fishery resources requires knowledge of their spatial distribution and notably of their critical life history stages. Predictive modelling of the European hake (Merluccius merluccius L., 1758) distribution was developed in the south-central Mediterranean Sea by means of historical fisheries-independent databases available in the region. The study area included the international waters of the south-central Mediterranean Sea and the territorial waters of Italy, Malta, Tunisia and Libya. Distribution maps of predicted population abundance index, and probabilistic occurrence of recruits and large adults were obtained by means of generalized additive …
Rheological, mechanical and morphological characterization of monopolymer blends made by virgin and photo-oxidized polypropylene
2021
In this work, monopolymer blends of virgin polypropylene and photo-oxidized polypropylene were prepare and characterized. The polypropylene samples were subjected to accelerated ageing to simulate the effects of outdoor exposure of polypropylene. After exposure, samples were pelletized and mixed with the same virgin polymer. The rheological, mechanical and morphological characterization was conducted on both the polymers and the blends. Both viscosity and mechanical properties decrease with increases in the content of recycled, photo-oxidized components and of the level of degradation of this component. In addition, the experimental data were compared with a model that takes into account bo…
GAMLSS for high-variability data: an application to liver fibrosis case
2020
In this paper, we propose management of the problem caused by overdispersed data by applying the generalized additive model for location, scale and shape framework (GAMLSS) as introduced by Rigby and Stasinopoulos (2005). The idea of using a GAMLSS approach for handling our problem comes from the idea of Aitkin (1996) consisting in the use of an EM maximum likelihood estimation algorithm (Dempster, Laird, and Rubin, 1977) to deal with overdispersed generalized linear models (GLM). As in the GLM case, the algorithm is initially derived as a form of Gaussian quadrature assuming a normal mixing distribution. The GAMLSS specification allows the extension of the Aitkin algorithm to probability d…
Illegal fishing in Isla del Coco National Park: Spatial-temporal distribution and the economic trade-offs
2020
Abstract The Isla del Coco National Park, located on the Pacific coast of Costa Rica, is rich in biodiversity and has a high concentration of pelagic species. This high marine biodiversity makes the Isla del Coco National Park (PNIC) a very attractive place for illegal fishers. We analyzed a dataset covering 8 years (2003–2010) of patrol records from PNIC with the aim of determining, a) the spatial-temporal distribution of illegal fishing, b) other areas that could be prone to illegal fishing but are currently undetected, c) the most profitable areas for this activity and d) the economic trade-offs of this illegal activity in relation to potential gains and the costs. Residuals Autocovariat…
Space-Time FPCA Clustering of Multidimensional Curves.
2018
In this paper we focus on finding clusters of multidimensional curves with spatio-temporal structure, applying a variant of a k-means algorithm based on the principal component rotation of data. The main advantage of this approach is to combine the clustering functional analysis of the multidimensional data, with smoothing methods based on generalized additive models, that cope with both the spatial and the temporal variability, and with functional principal components that takes into account the dependency between the curves.