Search results for "regression"
showing 10 items of 2619 documents
Prevalence and Time Trends in Myopia Among Children and Adolescents.
2020
Background Myopia (near-sightedness) is increasing worldwide, especially in Asia. The aim of this study was to describe trends in the prevalence of myopia in Germany. Methods We analyzed data from the German Health Interview and Examination Survey for Children and Adolescents (KiGGS; baseline survey 2003-2006, N = 17 640; wave 2, 2014-2017, N = 15 023). The presence of myopia was determined from a parent questionnaire and validated by the use of a visual aid. The population prevalence of myopia was calculated. Based on the KiGGS wave 2 data, potential risk factors for myopia were identified by means of logistic regression. Results The prevalence of myopia at the age of 0-17 years in Germany…
The sit up test to exhaustion as a test for muscular endurance evaluation
2015
Aims/Hypothesis The aim of this study was to examine the sit up test to exhaustion as a field test for muscular endurance evaluation in a sample of sedentary people of both sexes. Methods A cross-sectional study was performed. Three-hundred-eighty-one participants volunteered for the study (28.5 ± 10.0 years; 168.2 ± 8.9 cm; 65.1 ± 11.1 kg), of which 194 males (27.5 ± 10.2 years; 173.6 ± 7.0 cm; 71.2 ± 5.2 kg) and 187 females (29.6 ± 10.1 years; 162.6 ± 7.1 cm; 58.7 ± 8.9 kg). Each subject voluntarily and randomly performed: a sit up test (SUT), a push up test (PUT), and a free weight squat test (ST), all till exhaustion. A multiple regression analysis was adopted for data analysis. Subsequ…
Evaluation of Disaggregation Methods for Downscaling MODIS Land Surface Temperature to Landsat Spatial Resolution in Barrax Test Site
2016
Thermal infrared (TIR) data are usually acquired at a coarser spatial resolution (CR) than visible and near infrared (VNIR). Several disaggregation methods have been recently developed to enhance the TIR spatial resolution using VNIR data. These approaches are based on the retrieval of a relation between TIR and VNIR data at CR, or training of a neural network, to be applied at the fine resolution afterward. In this work, different disaggregation methods are applied to the combination of two different sensors in the experimental test site of Barrax, Spain. The main objective is to test the feasibility of these techniques when applied to satellites provided with no TIR bands. Landsat and mod…
Trends in phenological parameters and relationship between land surface phenology and climate data in the Hyrcanian forests of Iran
2017
Vegetation activity may be changed in response to climate variability by affecting seasonality and phenological events. Monitoring of land surface phenological changes play a key role in understanding feedback of ecosystem dynamics. This study focuses on the analysis of trends in land surface phenology derived parameters using normalized difference vegetation index time series based on Global Inventory Monitoring and Mapping Studies data in the Hyrcanian forests of Iran covering the period 1981–2012. First, we applied interpolation for data reconstruction in order to remove outliers and cloud contamination in time series. Phenological parameters were retrieved by using the midpoint approach…
Improving spatial temperature estimates by resort to time autoregressive processes
2012
Temperature estimation methods usually involve regression followed by kriging of residuals (residual kriging). Despite the performance of such models, there is invariably a residual which is not necessarily unpredictable because it may still be correlated in time. We set out to analyse such residuals through resort to autoregressive processes. It is shown that the optimal period varies depending on whether it is identified by functions of the form resd = f(resd−1, resd−2, ..., resd−p) or by partial correlations. Autoregressive processes significantly improve estimates, which are evaluated by cross-validations. Finally, the two following points are discussed: (1) the assumptions of the autor…
Temperature interpolation by local information ; the example of France
2010
International audience; Methods of interpolation, whether based on regressions or on kriging, are global methods in which all the available data for a given study area are used. But the quality of results is affected when the study area is spatially very heterogeneous. To overcome this difficulty, a method of local interpolation is proposed and tested here with temperature in France. Starting from a set of weather stations spread across the country and digitized as 250 m-sided cells, the method consists in modelling local spatial variations in temperature by considering each point of the grid and the n weather stations that are its nearest neighbours. The procedure entails a series of steps…
Gaussian Process Sensitivity Analysis for Oceanic Chlorophyll Estimation
2017
Source at https://doi.org/10.1109/JSTARS.2016.2641583. Gaussian process regression (GPR) has experienced tremendous success in biophysical parameter retrieval in the past years. The GPR provides a full posterior predictive distribution so one can derive mean and variance predictive estimates, i.e., point-wise predictions and associated confidence intervals. GPR typically uses translation invariant covariances that make the prediction function very flexible and nonlinear. This, however, makes the relative relevance of the input features hardly accessible, unlike in linear prediction models. In this paper, we introduce the sensitivity analysis of the GPR predictive mean and variance functions…
Exploring the linkage between dew point temperature and precipitation extremes: A multi-time-scale analysis on a semi-arid Mediterranean region
2021
Abstract Understanding warming climate implications on precipitation is of crucial importance, especially for areas particularly subjected to climate changes and land use/cover modifications, which could be extremely vulnerable to phenomena typically caused by rainfall extremes, such as floods and landslides. Past decade has been witnessing an increasing interest on simple modeling approaches based on the observation of commonly available meteorological variables and their physical linkages. In particular, based on the well-known thermodynamic Clausius-Clapeyron (CC) equation, it was widely investigated the scaling relation between rainfall extremes and variables representative of the near …
Oceanic and atmospheric linkages with short rainfall season intraseasonal statistics over Equatorial Eastern Africa and their predictive potential
2014
Despite earlier studies over various parts of the world including equatorial Eastern Africa (EEA) showing that intraseasonal statistics of wet and dry spells have spatially coherent signals and thus greater predictability potential, no attempts have been made to identify the predictors for these intraseasonal statistics. This study therefore attempts to identify the predictors (with a 1-month lead time) for some of the subregional intraseasonal statistics of wet and dry spells (SRISS) which showed the greatest predictability potential during the short rainfall season over EEA. Correlation analysis between the SRISS and seasonal rainfall totals on one hand and the predefined predictors on th…
REGEOTOP: New climatic data fields for East Asia based on localized relief information and geostatistical methods
2004
Climate data fields represent essential tools for climate, biogeographical and agricultural research to run models and to provide observational data for the verification of global climate models (GCM). Climate data fields are generated through interpolation of observations taken at meteorological stations. Most current interpolation procedures try to describe the influence of topography on spatial climatic variations by relating them directly to absolute elevation or by introducing simple relief variables such as exposure. In both cases this may not properly describe spatial climatic variations, particularly not those of precipitation. This paper describes a regionalization procedure (REGEO…