Search results for "Nonparametric regression"
showing 9 items of 9 documents
Social capital and economic growth in Europe: nonlinear trends and heterogeneous regional effects
2016
After two decades of academic debate on the social capital-growth nexus, discussion still remains open. Most of the literature so far, however, has followed the one-size-its-all approach, neglecting that the great disparities across geographical units might have implications in this relationship. This article analyzes the role of two social capital indicators on the growth of 237 European regions in the period 1995–2007 by implementing a set of both parametric and non- parametric regressions. Whereas the former impose a linear functional form for the parameters, the latter relax this assumption providing a flexible frame in which the functional form is given by the data. The technique also …
Functional Data Analysis and Mixed Effect Models
2004
Panel studies in econometrics as well as longitudinal studies in biomedical applications provide data from a sample of individual units where each unit is observed repeatedly over time (age, etc.). In this context, mixed effect models are often applied to analyze the behavior of a response variable in dependence of a number of covariates. In some important applications it is necessary to assume that individual effects vary over time (age, etc.).
Model-Assisted Estimation Through Random Forests in Finite Population Sampling
2021
In surveys, the interest lies in estimating finite population parameters such as population totals and means. In most surveys, some auxiliary information is available at the estimation stage. This information may be incorporated in the estimation procedures to increase their precision. In this article, we use random forests (RFs) to estimate the functional relationship between the survey variable and the auxiliary variables. In recent years, RFs have become attractive as National Statistical Offices have now access to a variety of data sources, potentially exhibiting a large number of observations on a large number of variables. We establish the theoretical properties of model-assisted proc…
Revisiting the quiet life hypothesis in banking using nonparametric techniques
2014
Early studies testing the quiet life hypothesis in banking found strong evidence that banks in more concentrated markets exhibit lower cost efficiency levels. More recent studies have reexamined the issue in different contexts, with mixed results. These approaches are based on stipulating a linear re- lationship between market power and efficiency in banking, which might be problematic, as suggested by the literature on efficiency analysis. We explore how bank cost efficiency measures are related to market power using flexible techniques, which are more consistent with those employed to measure efficiency in the first stage of the analysis. Our study focuses on the Spanish banking industry,…
B-Spline Estimation in a Survey Sampling Framework
2021
Nonparametric regression models have been used more and more over the last years to model survey data and incorporate efficiently auxiliary information in order to improve the estimation of totals, means or other study parameters such as Gini index or poverty rate. B-spline nonparametric regression has the benefit of being very flexible in modeling nonlinear survey data while keeping many similarities and properties of the classical linear regression. This method proved to be efficient for deriving a unique system of weights which allowed to estimate in an efficient way and simultaneously many study parameters. Applications on real and simulated survey data showed its high efficiency. This …
Estimating growth charts via nonparametric quantile regression: a practical framework with application in ecology.
2013
We discuss a practical and effective framework to estimate reference growth charts via regression quantiles. Inequality constraints are used to ensure both monotonicity and non-crossing of the estimated quantile curves and penalized splines are employed to model the nonlinear growth patterns with respect to age. A companion R package is presented and relevant code discussed to favour spreading and application of the proposed methods.
Joint Gaussian Processes for Biophysical Parameter Retrieval
2017
Solving inverse problems is central to geosciences and remote sensing. Radiative transfer models (RTMs) represent mathematically the physical laws which govern the phenomena in remote sensing applications (forward models). The numerical inversion of the RTM equations is a challenging and computationally demanding problem, and for this reason, often the application of a nonlinear statistical regression is preferred. In general, regression models predict the biophysical parameter of interest from the corresponding received radiance. However, this approach does not employ the physical information encoded in the RTMs. An alternative strategy, which attempts to include the physical knowledge, co…
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.
Crop nitrogen monitoring: Recent progress and principal developments in the context of imaging spectroscopy missions
2020
Abstract Nitrogen (N) is considered as one of the most important plant macronutrients and proper management of N therefore is a pre-requisite for modern agriculture. Continuous satellite-based monitoring of this key plant trait would help to understand individual crop N use efficiency and thus would enable site-specific N management. Since hyperspectral imaging sensors could provide detailed measurements of spectral signatures corresponding to the optical activity of chemical constituents, they have a theoretical advantage over multi-spectral sensing for the detection of crop N. The current study aims to provide a state-of-the-art overview of crop N retrieval methods from hyperspectral data…