Search results for "sampling"
showing 10 items of 788 documents
Validation procedures in radiological diagnostic models. Neural network and logistic regression
1999
The objective of this paper is to compare the performance of two predictive radiological models, logistic regression (LR) and neural network (NN), with five different resampling methods. One hundred and sixty-seven patients with proven calvarial lesions as the only known disease were enrolled. Clinical and CT data were used for LR and NN models. Both models were developed with cross validation, leave-one-out and three different bootstrap algorithms. The final results of each model were compared with error rate and the area under receiver operating characteristic curves (Az). The neural network obtained statistically higher Az than LR with cross validation. The remaining resampling validatio…
Nowcasting Global Economic Growth: A Factor-Augmented Mixed-Frequency Approach
2014
Facing several economic and financial uncertainties, assessing accurately global economic conditions is a great challenge for economists. The International Monetary Fund proposes within its periodic World Economic Outlook report a measure of the global GDP annual growth, that is often considered as the benchmark nowcast by macroeconomists. In this paper, we put forward an alternative approach to provide monthly nowcasts of the annual global growth rate. Our approach builds on a Factor-Augmented MIxed DAta Sampling (FA-MIDAS) model that enables (i) to account for a large monthly database including various countries and sectors of the global economy and (ii) to nowcast a low-frequency macroec…
Evaluation of the effect of chance correlations on variable selection using Partial Least Squares -Discriminant Analysis
2013
Variable subset selection is often mandatory in high throughput metabolomics and proteomics. However, depending on the variable to sample ratio there is a significant susceptibility of variable selection towards chance correlations. The evaluation of the predictive capabilities of PLSDA models estimated by cross-validation after feature selection provides overly optimistic results if the selection is performed on the entire set and no external validation set is available. In this work, a simulation of the statistical null hypothesis is proposed to test whether the discrimination capability of a PLSDA model after variable selection estimated by cross-validation is statistically higher than t…
Subcutaneous veins detection and backprojection method using Frangi vesselness filter
2015
Blood vessels detection is a common task performed in numerous medical procedures. During regular medical treatments venipuncture procedures are performed for invasive medication and blood sampling. Near infrared imaging technology can be used to visualize the subcutaneous veins in cases of difficult venous access. In this paper the methods for veins centerline detection and back projection is presented. In order to highlight the suitable veins for venipuncture, the centerline of larger veins are detected and back projected to the original image. The method is applied on the near infrared images of subjects selected from four different classes of skin tone. This can be helpful to medical st…
Efficient Dense Disparity Map Reconstruction using Sparse Measurements
2018
International audience; In this paper, we propose a new stereo matching algorithm able to reconstruct efficiently a dense disparity maps from few sparse disparity measurements. The algorithm is initialized by sampling the reference image using the Simple Linear Iterative Clustering (SLIC) superpixel method. Then, a sparse disparity map is generated only for the obtained boundary pixels. The reconstruction of the entire disparity map is obtained through the scanline propagation method. Outliers were effectively removed using an adaptive vertical median filter. Experimental results were conducted on the standard and the new Middlebury datasets show that the proposed method produces high-quali…
Spatial Coherence of Tropical Rainfall at the Regional Scale
2007
AbstractThis study examines the spatial coherence characteristics of daily station observations of rainfall in five tropical regions during the principal rainfall season(s): the Brazilian Nordeste, Senegal, Kenya, northwestern India, and northern Queensland. The rainfall networks include between 9 and 81 stations, and 29–70 seasons of observations. Seasonal-mean rainfall totals are decomposed in terms of daily rainfall frequency (i.e., the number of wet days) and mean intensity (i.e., the mean rainfall amount on wet days).Despite the diverse spatiotemporal sampling, orography, and land cover between regions, three general results emerge. 1) Interannual anomalies of rainfall frequency are us…
Sampling procedure in a willow plantation for estimation of moisture content
2015
Abstract Heating value and fuel quality of wood is closely connected to moisture content. In this work the variation of moisture content (MC) of short rotation coppice (SRC) willow shoots is described for five clones during one harvesting season. Subsequently an appropriate sampling procedure minimising labour costs and sampling uncertainty is proposed, where the MC of a single stem section with the length of 10–50 cm corresponds to the mean shoot moisture content (MSMC) with a bias of maximum 11 g kg −1 . This bias can be reduced by selecting the stem section according to the particular clone. The average difference in MSMC between the largest and smallest shoot in a stump was 31 g kg −1 .…
Joint probability distributions for wind speed and direction. A case study in Sicily
2015
In this study we analyze data of hourly average wind speed and direction measured at three different sampling stations located in Sicily (Italy) and provide a statistical model for their joint probability density function. Singly truncated from below Normal Weibull mixture distribution and a linear combination of von Mises distributions are used to model wind speed and direction. Sites with heterogeneous local conditions (prevailing wind direction and/or elevation) have been considered in order to investigate the reliability of the model here taken into consideration.
Spatial Bayesian Modeling Applied to the Surveys of Xylella fastidiosa in Alicante (Spain) and Apulia (Italy)
2020
The plant-pathogenic bacterium Xylella fastidiosa was first reported in Europe in 2013, in the province of Lecce, Italy, where extensive areas were affected by the olive quick decline syndrome, caused by the subsp. pauca. In Alicante, Spain, almond leaf scorch, caused by X. fastidiosa subsp. multiplex, was detected in 2017. The effects of climatic and spatial factors on the geographic distribution of X. fastidiosa in these two infested regions in Europe were studied. The presence/absence data of X. fastidiosa in the official surveys were analyzed using Bayesian hierarchical models through the integrated nested Laplace approximation (INLA) methodology. Climatic covariates were obtained from …
Contribution à l'estimation non paramétrique des quantiles géométriques et à l'analyse des données fonctionnelles
2008
In this dissertation we study the nonparametric geometric quantile estimation, conditional geometric quantiles estimation and functional data analysis. First, we are interested to the definition of geometric quantiles. Different simulations show that Transformation-Retransformation technique should be used to estimate geometric quantiles when the distribution is not spheric. A real study shows that, data are better modelized by geometric quantiles than by marginal one's, especially when variables that make up the random vector are correlated. Then we estimate geometric quantiles when data are obtained by survey sampling techniques. First, we propose an unbaised estimator, then using lineari…