Listar por autor UPNA "Militino, Ana F."
Mostrando ítems 1-20 de 20
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Age- and sex-specific spatio-temporal patterns of colorectal cancer mortality in Spain (1975-2008)
In this paper, space-time patterns of colorectal cancer (CRC) mortality risks are studied by sex and age group (50-69, ≥70) in Spanish provinces during the period 1975-2008. Space-time conditional autoregressive models are ... -
Búsqueda de submercados inmobiliarios mediante modelos de mixturas
(Gobierno de Navarra, Departamento de Economía y Hacienda, 2003) Contribución a congreso / Biltzarrerako ekarpenaLa heterogeneidad presente en el mercado inmobiliario dificulta enormemente su análisis y puede conllevar la presencia de submercados. En este caso, el modelo clásico de regresión lineal múltiple, ampliamente utilizado ... -
Checking unimodality using isotonic regression: an application to breast cancer mortality rates
In 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 ... -
Detecting change-points in the time series of surfaces occupied by pre-defined NDVI categories in continental Spain from 1981 to 2015
The free access to satellite images since more than 40 years ago has provoked a rapid increase of multitemporal derived information of remote sensing data that should be summarized and analyzed for future inferences. ... -
Estimación del desempleo por comarcas en Navarra
(Gobierno de Navarra, Departamento de Economía y Hacienda, 2005) Contribución a congreso / Biltzarrerako ekarpenaEl conocimiento del desempleo en una región es un indicador potente del ritmo de crecimiento de una economía, ya que de forma indirecta mide su capacidad para generar empleo. El Instituto de Estadística de Navarra está ... -
Estimating unemployment in very small areas
In the last few years, European countries have shown a deep interest in applying small area techniques to produce reliable estimates at county level. However, the specificity of every European country and the heterogeneity ... -
Filling missing data and smoothing altered data in satellite imagery with a spatial functional procedure
Outliers and missing data are commonly found in satellite imagery. These are usually caused by atmospheric or electronic failures, hampering the correct monitoring of remote-sensing data. To avoid distorted data, we propose ... -
Flexible Bayesian P-splines for smoothing age-specific spatio-temporal mortality patterns
In this paper age-space-time models based on one and two-dimensional P-splines with B-spline bases are proposed for smoothing mortality rates, where both xed relative scale and scale invariant two-dimensional penalties ... -
Improving the quality of satellite imagery based on ground-truth data from rain gauge stations
Multitemporal 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 ... -
Interpolation of the mean anomalies for cloud filling in land surface temperature and normalized difference vegetation index
When monitoring time series of remote sensing data, it is advisable to fill gaps, i.e., missing or distorted data, caused by atmospheric effects or technical failures. In this paper, a new method for filling these gaps ... -
An introduction to the spatio-temporal analysis of satellite remote sensing data for geostatisticians
Satellite remote sensing data have become available in meteorology, agriculture, forestry, geology, regional planning, hydrology or natural environment sciences since several decades ago, because satellites provide routinely ... -
Locally adaptive change-point detection (LACPD) with applications to environmental changes
We propose an adaptive-sliding-window approach (LACPD) for the problem of change-point detection in a set of time-ordered observations. The proposed method is combined with sub-sampling techniques to compensate for the ... -
Logistic regression versus XGBoost for detecting burned areas using satellite images
Classical statistical methods prove advantageous for small datasets, whereas machine learning algorithms can excel with larger datasets. Our paper challenges this conventional wisdom by addressing a highly significant ... -
Machine learning procedures for daily interpolation of rainfall in Navarre (Spain)
(Springer, 2023) Capítulo de libro / Liburuen kapituluaKriging is by far the most well known and widely used statistical method for interpolating data in spatial random fields. The main reason is that it provides the best linear unbiased predictor and it is an exact interpolator ... -
On the performances of trend and change-point detection methods for remote sensing data
Detecting change-points and trends are common tasks in the analysis of remote sensing data. Over the years, many different methods have been proposed for those purposes, including (modified) Mann-Kendall and Cox-Stuart ... -
Software tools and statistical methods for downloading, processing, and analysing satellite images
El principal objetivo de esta tesis es la introducción y desarrollo de métodos estadísticos en imágenes satelitales para mejorar el procesamiento, suavizado, predicción, e inferencia de los datos de teledetección. Este ... -
Stochastic spatio-temporal models for analysing NDVI distribution of GIMMS NDVI3g images
The 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 ... -
Tendencias en las tasas de incidencia de cáncer colorrectal en Navarra en el periodo 1990-2005
Fundamento. En España, se ha observado un aumento de la incidencia de cáncer colorrectal (CCR) en ambos sexos en los últimos años, posiblemente debido a las mejoras diagnósticas, a la occidentalización de la dieta y ... -
Unpaired spatio-temporal fusion of image patches (USTFIP) from cloud covered images
Spatio-temporal image fusion aims to increase the frequency and resolution of multispectral satellite sensor images in a cost-effective manner. However, practical constraints on input data requirements and computational ... -
Using RGISTools to estimate water levels in reservoirs and lakes
The combination of freely accessible satellite imagery from multiple programs improves the spatio-temporal coverage of remote sensing data, but it exhibits barriers regarding the variety of web services, file formats, and ...