Search results for "Spline"
showing 10 items of 170 documents
Modeling temperature effects on mortality: multiple segmented relationships with common break points.
2008
We present a model for estimation of temperature effects on mortality that is able to capture jointly the typical features of every temperature-death relationship, that is, nonlinearity and delayed effect of cold and heat over a few days. Using a segmented approximation along with a doubly penalized spline-based distributed lag parameterization, estimates and relevant standard errors of the cold- and heat-related risks and the heat tolerance are provided. The model is applied to data from Milano, Italy.
Analyzing Temperature Effects on Mortality Within theREnvironment: The Constrained Segmented Distributed Lag Parameterization
2010
Here we present and discuss the R package modTempEff including a set of functions aimed at modelling temperature effects on mortality with time series data. The functions fit a particular log linear model which allows to capture the two main features of mortality- temperature relationships: nonlinearity and distributed lag effect. Penalized splines and segmented regression constitute the core of the modelling framework. We briefly review the model and illustrate the functions throughout a simulated dataset.
Fitting generalized linear models with unspecified link function: A P-spline approach
2008
Generalized linear models (GLMs) outline a wide class of regression models where the effect of the explanatory variables on the mean of the response variable is modelled throughout the link function. The choice of the link function is typically overlooked in applications and the canonical link is commonly used. The estimation of GLMs with unspecified link function is discussed, where the linearity assumption between the link and the linear predictor is relaxed and the unspecified relationship is modelled flexibly by means of P-splines. An estimating algorithm is presented, alternating estimation of two working GLMs up to convergence. The method is applied to the analysis of quit behavior of…
Multiple smoothing parameters selection in additive regression quantiles
2021
We propose an iterative algorithm to select the smoothing parameters in additive quantile regression, wherein the functional forms of the covariate effects are unspecified and expressed via B-spline bases with difference penalties on the spline coefficients. The proposed algorithm relies on viewing the penalized coefficients as random effects from the symmetric Laplace distribution, and it turns out to be very efficient and particularly attractive with multiple smooth terms. Through simulations we compare our proposal with some alternative approaches, including the traditional ones based on minimization of the Schwarz Information Criterion. A real-data analysis is presented to illustrate t…
Comparison between splines and fractional polynomials for multivariable model building with continuous covariates: a simulation study with continuous…
2012
In observational studies, many continuous or categorical covariates may be related to an outcome. Various spline-based procedures or the multivariable fractional polynomial (MFP) procedure can be used to identify important variables and functional forms for continuous covariates. This is the main aim of an explanatory model, as opposed to a model only for prediction. The type of analysis often guides the complexity of the final model. Spline-based procedures and MFP have tuning parameters for choosing the required complexity. To compare model selection approaches, we perform a simulation study in the linear regression context based on a data structure intended to reflect realistic biomedica…
Integral relations, a simplified method to find interfacial resistivities for heat and mass transfer.
2007
International audience; Integral relations were used to predict interface film transfer coefficients for evaporation and condensation. According to these, all coefficients can be calculated for one-component systems, using the thermal resistivity and the enthalpy profile through the interface. The expressions were verified in earlier work using non-equilibrium molecular dynamics simulations for argon-like particles, which interacted with a short-range Lennard-Jones (LJ) spline potential, which becomes zero at about 1.7 times the LJ-diameter. In this paper we verify the validity of these relations for a long-range LJ spline potential which becomes zero at 2.5 times the diameter. In an earlie…
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.
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.