# Functional convolution models

@article{Asencio2014FunctionalCM, title={Functional convolution models}, author={Maria Asencio and Giles Hooker and H. Oliver Gao}, journal={Statistical Modelling}, year={2014}, volume={14}, pages={315 - 335} }

This article considers the application of functional data analysis methods to modelling particulate matter emission profiles from dynamometer experiments. In particular the functional convolution model is introduced as an extension of the distributed lag model to functional (smooth and continuous) observations. We present a penalized ordinary least squares estimator for the model and a novel bootstrap procedure to provide pointwise confidence regions for the estimated convolution functions. The… Expand

#### 10 Citations

On the Identifiability of the Functional Convolution Model

- Mathematics
- 2013

This report details conditions under which the Functional Convolution Model described in \citet{AHG13} can be identified from Ordinary Least Squares estimates without either dimension reduction or… Expand

Estimation in Functional Convolution Model

- 2021

The aim of the paper is to propose an estimator of the unknown function in the Functional Convolution Model (FCVM), which studies the relationship between a functional covariate X(t) and a functional… Expand

Truncated linear models for functional data

- Mathematics
- 2014

Summary
A conventional linear model for functional data involves expressing a response variable Y in terms of the explanatory function X(t), via the model , where a is a scalar, b is an unknown… Expand

Sparse Estimation of Historical Functional Linear Models with a Nested Group Bridge Approach

- Mathematics
- 2019

The conventional historical functional linear model relates the current value of the functional response at time t to all past values of the functional covariate up to time t. Motivated by situations… Expand

Estimating Truncated Functional Linear Models With a Nested Group Bridge Approach

- Mathematics
- Journal of Computational and Graphical Statistics
- 2020

Abstract We study a scalar-on-function truncated linear regression model which assumes that the functional predictor does not influence the response when the time passes a certain cutoff point. We… Expand

A Functional Data Method for Causal Dynamic Network Modeling of Task-Related fMRI

- Computer Science, Medicine
- Front. Neurosci.
- 2019

This paper proposes a causal dynamic network (CDN) method to estimate brain activations and connections simultaneously in fMRI, which achieves higher estimation accuracy while improving the computational speed by from tens to thousands of times. Expand

Restricted likelihood ratio tests for linearity in scalar-on-function regression

- Mathematics, Computer Science
- Stat. Comput.
- 2015

This work proposes a procedure for testing the linearity of a scalar-on-function regression relationship and shows how the functional linear model can be represented as a simple mixed model nested within the FGAM, a recently developed extension of thefunctional linear model. Expand

Asymptotic analysis of microtubule-based transport by multiple identical molecular motors.

- Medicine, Mathematics
- Journal of theoretical biology
- 2012

Through an asymptotic analysis of a system of SDEs, a means for applying in vitro observations of the nonlinear response by motors to forces induced on the attached cargo is developed to make analytical predictions for two parameter regimes that have thus far eluded direct experimental observation. Expand

Functional linear regression models : application to high-throughput plant phenotyping functional data

- Physics
- 2016

L'Analyse des Donnees Fonctionnelles (ADF) est une branche de la statistique qui est de plus en plus utilisee dans de nombreux domaines scientifiques appliques tels que l'experimentation biologique,… Expand

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This report details conditions under which the Functional Convolution Model described in \citet{AHG13} can be identified from Ordinary Least Squares estimates without either dimension reduction or… Expand

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