Search results for " P-spline"

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…

Long gaps in multivariate spatio-temporal data: an approach based on functional data analysis

2015

The main aim of this paper is to perform Functional Principal Component Analysis (FPCA) taking into account spatio-temporal correlation structures, in order to fill in missing values in spatio-temporal multivariate data set. A spatial and a spatio-temporal variant of the classical temporal FPCA is considered; in other words, FPCA is carried out after modeling data with respect to more than one dimension: space (long, lat) or space+time. Moreover, multidimensional FPCA is extended to multivariate context (more than one variable). Information on spatial or spatiotemporal structures are efficiently extracted by applying Generalized Additive Models (GAMs). Both simulation studies and some perfo…

P-spline quantile regression: a new algorithm for smoothing parameter selection

Comparing Spatial and Spatio-temporal FPCA to Impute Large Continuous Gaps in Space

2018

Multivariate spatio-temporal data analysis methods usually assume fairly complete data, while a number of gaps often occur along time or in space. In air quality data long gaps may be due to instrument malfunctions; moreover, not all the pollutants of interest are measured in all the monitoring stations of a network. In literature, many statistical methods have been proposed for imputing short sequences of missing values, but most of them are not valid when the fraction of missing values is high. Furthermore, the limitation of the methods commonly used consists in exploiting temporal only, or spatial only, correlation of the data. The objective of this paper is to provide an approach based …

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.

Adaptive smoothing spline using non-convex penalties

2022

We propose a new adaptive penalty for smoothing via penalized splines. The new form of adaptive penalization is based on penalizing the differences of the coefficients of adjacent bases, using non-convex penalties. This makes possible to estimate curves with varying amounts of smoothness. Comparisons with respect to some competitors are presented.