Browsing Applied Statistics by Title
Now showing items 56-71 of 71
-
Sample size impact on the categorisation of continuous variables in clinical prediction
Barrio, I.; Arostegui, I.
; Rodríguez-Álvarez, M.X. (2017-12)
Recent advances in information technologies are generating a growth in the amount of available biomedical data. In this paper, we studied the impact sample size may have on the categorisation of a continuous predictor ... -
A simple Bayesian linear excess relative risk model
(2017-07-11)A new Bayesian Poisson relative risk model is proposed for displaying the excess relative risk associated to a unique exposure as a probability distribution in a closed form. The background risk can be modelled by a unique ... -
Simulation approach for assessing the performance of the γEWMA control chart
(2021-02-22)i) Purpose: The purpose of this paper is to evaluate the performance of a modified EWMA control chart ($\gamma$EWMA control chart), which considers data distribution and incorporate its correlation structure, simulating ... -
Smooth additive mixed models for predicting aboveground biomass
Sánchez-González, M.; Durban, M.; Lee, D.-J.; Cañellas, I.; Sixto, H. (2016-12-01)
Aboveground biomass estimation in short-rotation forestry plantations is an essential step in the development of crop management strategies as well as allowing the economic viability of the crop to be determined prior to ... -
Spatial Bayesian Modeling Applied to the Surveys of Xylella fastidiosa in Alicante (Spain) and Apulia (Italy)
Cendoya, M.; Martínez-Minaya, J.; Dalmau, V.; Ferrer, A.; Saponari, M.; Conesa, D.; López-Quílez, A.; Vicent, A. (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. ... -
Spatial Models for Field Trials
Rodríguez-Álvarez, M.X.; Boer, M.P.; Eeuwijk, F.; Eilers, P.H.C. (2016-09-01)
An important aim of the analysis of agricultural field trials is to obtain good predictions for genotypic performance, by correcting for spatial effects. In practice these corrections turn out to be complicated, since there ... -
Spatio-temporal adaptive penalized splines with application to Neuroscience
Rodríguez-Álvarez, M.X.; Durban, M.; Lee, D.-J.; Eilers, P.H.C.; Gonzalez, F (2016-12-30)
Data analysed here derive from experiments conducted to study neurons' activity in the visual cortex of behaving monkeys. We consider a spatio-temporal adaptive penalized spline (P-spline) approach for modelling the firing ... -
Spatio-temporal functional data analysis for wireless sensor networks data
Lee, D.-J.; Zhu, Z.; Toscas, P. (2015-05-05)
A new methodology is proposed for the analysis, modeling, and forecasting of data collected from a wireless sensor network. Our approach is considered in the framework of a functional data-analysis paradigm where observed ... -
A statistical framework for radiation dose estimation with uncertainty quantification from the γ-H2AX assay
(2018-11-28)Over the last decade, the γ–H2AX focus assay, which exploits the phosphorylation of the H2AX histone following DNA double–strand–breaks, has made considerable progress towards acceptance as a reliable biomarker for exposure ... -
A survey of bias in machine learning through the prism of statistical parity
Besse, P.; del Barrio, E.; Gordaliza, P.; Loubes, J.-M.; Risser, L. (2020)
Applications based on machine learning models have now become an indispensable part of the everyday life and the professional world. As a consequence, a critical question has recently arose among the population: Do algorithmic ... -
Time resolved amplified FRET identifies protein kinase B activation state as a marker for poor prognosis in clear cell renal cell carcinoma
Miles, J.; Applebee, C.J.; Leboucher, P.; Lopez-Fernandez, S.; Lee, D.-J.; Guarch, R.; Ward, S.; Parker, P.J.; López, J.I.; Larijani B (2017-12)
Purpose Clear cell Renal Cell Carcinomas (ccRCC), the largest group of renal tumours, are resistant to classical therapies. The determination of the functional state of actionable biomarkers for the assessment of these ... -
Time-varying coefficient estimation in SURE models. Application to portfolio management.
(2017-01-01)This paper provides a detailed analysis of the asymptotic properties of a kernel estimator for a Seemingly Unrelated Regression Equations model with time-varying coefficients (tv-SURE) under very general conditions. ... -
A two-stage approach for the spatio-temporal analysis of high-throughput phenotyping data
Pérez, D.M.; Rodríguez-Álvarez, M.X.; Boer, M.P; Kronenberg, L.; Hund, A.; Cabrera-Bosquet, L.; Millet, E.J.; van Eeuwijk, F.A. (2022-02-24)
High throughput phenotyping (HTP) platforms and devices are increasingly used for the characterization of growth and developmental processes for large sets of plant genotypes. Such HTP data require challenging statistical ... -
Uncertainty on radiation doses estimated by biological and retrospective physical methods
(2017-09-18)Biological and physical retrospective dosimetry are recognised as key techniques to provide individual estimates of dose following unplanned exposures to ionising radiation. Whilst there has been a relatively large amount ... -
Variable selection in high-dimensional data: application in a SARS-CoV-2 pneumonia clinical data-set
(2021-09-15)As a result of the COVID-19 pandemic that collapsed hospitals in some countries, numerous studies have been carried out to understand the development of the disease and how it affects patients with different characteristics, ...