Artículos de revista DEIO - EIOS Aldizkari artikuluak
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Browsing Artículos de revista DEIO - EIOS Aldizkari artikuluak by Department/Institute "Institute for Advanced Materials and Mathematics - INAMAT2"
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Publication Open Access Checking unimodality using isotonic regression: an application to breast cancer mortality rates(Springer, 2016) Rueda, C.; Ugarte Martínez, María Dolores; Militino, Ana F.; Estatistika eta Ikerketa Operatiboa; Institute for Advanced Materials and Mathematics - INAMAT2; Estadística e Investigación OperativaIn some diseases it is well-known that a unimodal mortality pattern exists. A clear example in developed countries is breast cancer, where mortality increased sharply until the nineties and then decreased. This clear unimodal pattern is not necessarily applicable to all regions within a country. In this paper, we develop statistical tools to check if the unimodality pattern persists within regions using order restricted inference. Break points as well as confidence intervals are also provided. In addition, a new test for checking monotonicity against unimodality is derived allowing to discriminate between a simple increasing pattern and an up-then-down response pattern. A comparison with the widely used joinpoint regression technique under unimodality is provided. We show that the joinpoint technique could fail when the underlying function is not piecewise linear. Results will be illustrated using age-specific breast cancer mortality data from Spain in the period 1975-2005.Publication Open Access Evaluation of grape stems and grape stem extracts for sulfur dioxide replacement during grape wine production(Elsevier, 2023) Pires Nogueira, Danielle; Jiménez Moreno, Nerea; Esparza Catalán, Irene; Moler Cuiral, José Antonio; Ferreira-Santos, Pedro; Sagüés Sarasa, Ana; Teixeira, José António; Ancín Azpilicueta, Carmen; Ciencias; Zientziak; Estadística e Investigación Operativa; Estatistika eta Ikerketa Operatiboa; Institute for Advanced Materials and Mathematics - INAMAT2Sulfur dioxide (SO2), the main preservative in wine, may affect the sensory properties of the wines, as well as cause allergic reactions and headaches in sensitive people. The aim of this work was to evaluate the replacement of SO2 in Tempranillo wines with Mazuelo grape stem products. Five Tempranillo red wines were elaborated: positive control (60 mg/L SO2); negative control with no preservatives; Mazuelo extract (200 mg/L); Mazuelo extract combined with SO2 (100 mg/L + 20 mg/L); and Mazuelo stem (400 mg/L). The oenological parameters, antioxidant capacity, total phenolic (TP), total flavonoids (TF) and total anthocyanins (TA) contents were determined. Additionally, individual phenols were analyzed by HPLC-DAD-FLD. The spectrophotometric analyses showed that the wines had similar antioxidant capacities and concentrations of TP and TF. However, TA was more affected by the lack of SO2 as anthocyanins presented higher concentrations in positive control samples. The concentrations of individual phenols followed a similar path in all samples. Wines containing sulfites were more similar than the other treatments. However, these similarities were not reflected on the sensory analysis performed, as triangle test did not show differences between the wine with extract addition and the positive control wine. Therefore, Mazuelo stem extract could be a possible strategy for SO2 replacement. Nevertheless, further studies are necessary to confirm the potential of grape stem extracts as wine preservative.Publication Open Access Improving the quality of satellite imagery based on ground-truth data from rain gauge stations(MDPI, 2018) Militino, Ana F.; Ugarte Martínez, María Dolores; Pérez Goya, Unai; Estatistika eta Ikerketa Operatiboa; Institute for Advanced Materials and Mathematics - INAMAT2; Estadística e Investigación Operativa; Gobierno de Navarra / Nafarroako GobernuaMultitemporal imagery is by and large geometrically and radiometrically accurate, but the residual noise arising from removal clouds and other atmospheric and electronic effects can produce outliers that must be mitigated to properly exploit the remote sensing information. In this study, we show how ground-truth data from rain gauge stations can improve the quality of satellite imagery. To this end, a simulation study is conducted wherein different sizes of outlier outbreaks are spread and randomly introduced in the normalized difference vegetation index (NDVI) and the day and night land surface temperature (LST) of composite images from Navarre (Spain) between 2011 and 2015. To remove outliers, a new method called thin-plate splines with covariates (TpsWc) is proposed. This method consists of smoothing the median anomalies with a thin-plate spline model, whereby transformed ground-truth data are the external covariates of the model. The performance of the proposed method is measured with the square root of the mean square error (RMSE), calculated as the root of the pixel-by-pixel mean square differences between the original data and the predicted data with the TpsWc model and with a state-space model with and without covariates. The study shows that the use of ground-truth data reduces the RMSE in both the TpsWc model and the state-space model used for comparison purposes. The new method successfully removes the abnormal data while preserving the phenology of the raw data. The RMSE reduction percentage varies according to the derived variables (NDVI or LST), but reductions of up to 20% are achieved with the new proposal.Publication Open Access Prostate cancer incidence and mortality in Navarre (Spain)(Gobierno de Navarra. Departamento de Salud, 2018) Etxeberria Andueza, Jaione; Guevara Eslava, Marcela; Moreno Iribas, Conchi; Burgui, Rosana; Delfrade Osinaga, J.; Floristan, Y.; Montesino Semper, Manuel F.; Ardanaz, Eva; Estatistika eta Ikerketa Operatiboa; Institute for Advanced Materials and Mathematics - INAMAT2; Estadística e Investigación OperativaFundamento. A nivel mundial, el cáncer de próstata es uno de los tumores malignos más comúnmente diagnosticados en los hombres. En este estudio, se analizan las tendencias de la incidencia y mortalidad de cáncer de próstata, global y por grupos de edad, para mostrar la situación epidemiológica pasada y actual de la enfermedad en Navarra (España). Método. Para el estudio se utilizaron los casos incidentes diagnosticados entre 1975 y 2010, y las muertes observadas entre 1975 y 2013. Los datos fueron proporcionados por el Registro de Cáncer de Navarra y el Instituto Nacional de Estadística respectivamente. Se calcularon las tasas de incidencia y mortalidad estandarizadas por edad, los puntos de cambio y el porcentaje de cambio anual (PCA) mediante modelos de regresión de joinpoint. Se usaron modelos unidimensionales de P-splines para estimar proyecciones hasta 2016. Resultados. Se observó un considerable incremento en las tasas de incidencia de cáncer de próstata en hombres de 45-74 años, con PCA de +4,5% (p<0,001), +9,5% (p<0,001) y +2,4% (p<0,05) en los periodos 1975-1990, 1990-2000 y 2000- 2010, respectivamente. En el grupo de mayores de 74 se registró un aumento de incidencia en el período 1975-1999 (PCA +3,3%, p<0,001), seguido de una disminución significativa hasta 2010 (PCA -4,0%, p<0,01). Las tasas de mortalidad aumentaron hasta 1995 (PCA +2,2%, p<0,001), mientras que descendieron en el periodo 1995-2013 (PCA -3.4%, p<0,001). Conclusión. Aunque las tasas globales de incidencia de cáncer de próstata parecen estabilizarse en 2002-2010 en Navarra, las tendencias fueron diferentes según los grupos de edad, aumentando en los hombres de 45-74 años y disminuyendo en el grupo de mayores de 74 años. Se observó una disminución en las tasas de mortalidad en ambos grupos de edad desde 1995. Cambios en el uso del antígeno prostático específico para cribado en los próximos años podrían afectar las futuras tendencias del cáncer de próstata. Palabras clave. Cáncer de Próstata. Incidencia. Mortalidad. Estimaciones. TendenciasPublication Open Access Small area estimation of gender-based violence: rape incidence risks in Uttar Pradesh, India(Society of Statistics, Computer and Applications, 2018) Vicente Fuenzalida, Gonzalo; Goicoa Mangado, Tomás; Puranik, A; Ugarte Martínez, María Dolores; Estatistika eta Ikerketa Operatiboa; Institute for Advanced Materials and Mathematics - INAMAT2; Estadística e Investigación OperativaViolence against women is considered an endemic problem in communities and countries around the world, and it has been declared an issue of epidemic proportions by the World Health Organization (WHO). In India, where the patriarchal nature of the country contributes to increasing violence against women, there has been a dramatic increase of this gender-based violence in the past decades. In this paper we focus on analyzing rape incidence risks in the most populous state of India. In particular, small area models including spatial, temporal, and spatio-temporal components are used to estimate rape incidence risks in the districts of Uttar Pradesh during the period 2001-2014. We discover interesting spatio-temporal patterns of rape incidence as well as point out districts with significant high risks.Publication Open Access Spatial gender-age-period-cohort analysis of pancreatic cancer mortality in Spain (1990-2013)(Public Library of Science, 2017) Etxeberria Andueza, Jaione; Goicoa Mangado, Tomás; López Abente, Gonzalo; Riebler, Andrea; Ugarte Martínez, María Dolores; Estatistika eta Ikerketa Operatiboa; Institute for Advanced Materials and Mathematics - INAMAT2; Estadística e Investigación Operativa; Gobierno de Navarra / Nafarroako Gobernua, 113, Res.2186/2014Recently, the interest in studying pancreatic cancer mortality has increased due to its high lethality. In this work a detailed analysis of pancreatic cancer mortality in Spanish provinces was performed using recent data. A set of multivariate spatial gender-age-period-cohort models was considered to look for potential candidates to analyze pancreatic cancer mortality rates. The selected model combines features of APC (age-period-cohort) models with disease mapping approaches. To ensure model identifiability sum-to-zero constraints were applied. A fully Bayesian approach based on integrated nested Laplace approximations (INLA) was considered for model fitting and inference. Sensitivity analyses were also conducted. In general, estimated average rates by age, cohort, and period are higher in males than in females. The higher differences according to age between males and females correspond to the age groups [65, 70), [70, 75), and [75, 80). Regarding the cohort, the greatest difference between men and women is observed for those born between the forties and the sixties. From there on, the younger the birth cohort is, the smaller the difference becomes. Some cohort differences are also identified by regions and age-groups. The spatial pattern indicates a North-South gradient of pancreatic cancer mortality in Spain, the provinces in the North being the ones with the highest effects on mortality during the studied period. Finally, the space-time evolution shows that the space pattern has changed little over time.Publication Open Access Stochastic spatio-temporal models for analysing NDVI distribution of GIMMS NDVI3g images(MDPI, 2017) Militino, Ana F.; Ugarte Martínez, María Dolores; Pérez Goya, Unai; Estatistika eta Ikerketa Operatiboa; Institute for Advanced Materials and Mathematics - INAMAT2; Estadística e Investigación Operativa; Gobierno de Navarra / Nafarroako Gobernua: Project PI015, 2016The normalized difference vegetation index (NDVI) is an important indicator for evaluating vegetation change, monitoring land surface fluxes or predicting crop models. Due to the great availability of images provided by different satellites in recent years, much attention has been devoted to testing trend changes with a time series of NDVI individual pixels. However, the spatial dependence inherent in these data is usually lost unless global scales are analyzed. In this paper, we propose incorporating both the spatial and the temporal dependence among pixels using a stochastic spatio-temporal model for estimating the NDVI distribution thoroughly. The stochastic model is a state-space model that uses meteorological data of the Climatic Research Unit (CRU TS3.10) as auxiliary information. The model will be estimated with the Expectation-Maximization (EM) algorithm. The result is a set of smoothed images providing an overall analysis of the NDVI distribution across space and time, where fluctuations generated by atmospheric disturbances, fire events, land-use/cover changes or engineering problems from image capture are treated as random fluctuations. The illustration is carried out with the third generation of NDVI images, termed NDVI3g, of the Global Inventory Modeling and Mapping Studies (GIMMS) in continental Spain. This data are taken in bymonthly periods from January 2011 to December 2013, but the model can be applied to many other variables, countries or regions with different resolutions.Publication Open Access Temporal evolution of brain cancer incidence in the municipalities of Navarre and the Basque Country, Spain(BioMed Central, 2015) Ugarte Martínez, María Dolores; Adin Urtasun, Aritz; Goicoa Mangado, Tomás; Casado, Itziar; Ardanaz, Eva; Larrañaga, Nerea; Estatistika eta Ikerketa Operatiboa; Institute for Advanced Materials and Mathematics - INAMAT2; Estadística e Investigación Operativa; Gobierno de Navarra / Nafarroako Gobernua: proyecto 113 Res. 2186/2014Background: Brain cancer incidence rates in Spain are below the European’s average. However, there are two regions in the north of the country, Navarre and the Basque Country, ranked among the European regions with the highest incidence rates for both males and females. Our objective here was two-fold. Firstly, to describe the temporal evolution of the geographical pattern of brain cancer incidence in Navarre and the Basque Country, and secondly, to look for specific high risk areas (municipalities) within these two regions in the study period (1986–2008). Methods: A mixed Poisson model with two levels of spatial effects is used. The model also included two levels of spatial effects (municipalities and local health areas). Model fitting was carried out using penalized quasi-likelihood. High risk regions were detected using upper one-sided confidence intervals. Results: Results revealed a group of high risk areas surrounding Pamplona, the capital city of Navarre, and a few municipalities with significant high risks in the northern part of the region, specifically in the border between Navarre and the Basque Country (Gipuzkoa). The global temporal trend was found to be increasing. Differences were also observed among specific risk evolutions in certain municipalities. Conclusions: Brain cancer incidence in Navarre and the Basque Country (Spain) is still increasing with time. The number of high risk areas within those two regions is also increasing. Our study highlights the need of continuous surveillance of this cancer in the areas of high risk. However, due to the low percentage of cases explained by the known risk factors, primary prevention should be applied as a general recommendation in these populations.