Search results for " regression [Classificació AMS]"
showing 10 items of 162 documents
Landform classification: a high-performing mapping unit partitioning tool for landslide susceptibility assessment—a test in the Imera River basin (no…
2022
In landslide susceptibility studies, the type of mapping unit adopted affects the obtained models and maps in terms of accuracy, robustness, spatial resolution and geomorphological adequacy. To evaluate the optimal selection of these units, a test has been carried out in an important catchment of northern Sicily (the Imera River basin), where the spatial relationships between a set of predictors and an inventory of 1608 rotational/translational landslides were analysed using the multivariate adaptive regression splines (MARS) method. In particular, landslide susceptibility models were prepared and compared by adopting four different types of mapping units: the largely adopted grid cells (PX…
Application of molecular topology to the prediction of antiparasitic activity against Giardia intestinalis and Trichomonas vaginalis of 2-Acylamino-n…
2020
Giardia intestinalis y Trichomonas vaginalis destacan por su importancia clínica. G. intestinalis causa la giardiosis, una parasitosis de gran importancia epidemiológica y clínica por presentar una elevada prevalencia. T. vaginalis causa la tricomoniasis, la enfermedad de transmisión sexual (ETS) no viral con mayor incidencia del mundo. Ambas parasitosis comparten el mismo tratamiento farmacológico: los nitroimidazoles. Se ha aplicado la topología molecular en la búsqueda de derivados del 2-Acylamino-nitro-1,3-tiazol con actividad antiparasitaria frente a G. intestinalis y T. vaginalis . Con el análisis lineal discriminante se obtuvo un modelo capaz de clasificar correctamente el 92,85 % de…
Multiple linear regression analysis of RF values of chlorinated catechols and guaiacols
1981
The multiple linear regression analysis of the RF values of chlorinated catechols and guaiacols has been carried out. The resolved terms, in the regression equation have been used to explain the relative mobility of chlorinated compounds to the reference compound (catechol or guaiacol). The best correlations have been observed for solvent systems which give the greatest standard deviations and relative differences between the RF values. A good correlation between the standard deviation of the RF values and the term which represents the effect of the chlorine atom ortho to the hydroxyl group(s) have also been observed.
A penalized approach to covariate selection through quantile regression coefficient models
2019
The coefficients of a quantile regression model are one-to-one functions of the order of the quantile. In standard quantile regression (QR), different quantiles are estimated one at a time. Another possibility is to model the coefficient functions parametrically, an approach that is referred to as quantile regression coefficients modeling (QRCM). Compared with standard QR, the QRCM approach facilitates estimation, inference and interpretation of the results, and generates more efficient estimators. We designed a penalized method that can address the selection of covariates in this particular modelling framework. Unlike standard penalized quantile regression estimators, in which model selec…
Marginal hazard ratio estimates in joint frailty models for heart failure trials
2019
Abstract This work is motivated by clinical trials in chronic heart failure disease, where treatment has effects both on morbidity (assessed as recurrent non‐fatal hospitalisations) and on mortality (assessed as cardiovascular death, CV death). Recently, a joint frailty proportional hazards model has been proposed for these kind of efficacy outcomes to account for a potential association between the risk rates for hospital admissions and CV death. However, more often clinical trial results are presented by treatment effect estimates that have been derived from marginal proportional hazards models, that is, a Cox model for mortality and an Andersen–Gill model for recurrent hospitalisations. …
Sparse relative risk regression models
2020
Summary Clinical studies where patients are routinely screened for many genomic features are becoming more routine. In principle, this holds the promise of being able to find genomic signatures for a particular disease. In particular, cancer survival is thought to be closely linked to the genomic constitution of the tumor. Discovering such signatures will be useful in the diagnosis of the patient, may be used for treatment decisions and, perhaps, even the development of new treatments. However, genomic data are typically noisy and high-dimensional, not rarely outstripping the number of patients included in the study. Regularized survival models have been proposed to deal with such scenarios…
Parametric estimation of non-crossing quantile functions
2021
Quantile regression (QR) has gained popularity during the last decades, and is now considered a standard method by applied statisticians and practitioners in various fields. In this work, we applied QR to investigate climate change by analysing historical temperatures in the Arctic Circle. This approach proved very flexible and allowed to investigate the tails of the distribution, that correspond to extreme events. The presence of quantile crossing, however, prevented using the fitted model for prediction and extrapolation. In search of a possible solution, we first considered a different version of QR, in which the QR coefficients were described by parametric functions. This alleviated th…
Simulation in the Simple Linear Regression Model
2002
Summary This article presents an activity which simulates the linear regression model in order to verify the probabilistic behaviour of the resulting least-squares statistics in practice.
Varying-coefficient functional linear regression models
2008
This article considers a generalization of the functional linear regression in which an additional real variable influences smoothly the functional coefficient. We thus define a varying-coefficient regression model for functional data. We propose two estimators based, respectively, on conditional functional principal regression and on local penalized regression splines and prove their pointwise consistency. We check, with the prediction one day ahead of ozone concentration in the city of Toulouse, the ability of such nonlinear functional approaches to produce competitive estimations.
Estimating regression models with unknown break-points.
2003
This paper deals with fitting piecewise terms in regression models where one or more break-points are true parameters of the model. For estimation, a simple linearization technique is called for, taking advantage of the linear formulation of the problem. As a result, the method is suitable for any regression model with linear predictor and so current software can be used; threshold modelling as function of explanatory variables is also allowed. Differences between the other procedures available are shown and relative merits discussed. Simulations and two examples are presented to illustrate the method.