Functional Regression Using the fda Package in R

Functional Regression. Using the fda Package in R. Spencer Graves, Giles Hooker, James Ramsay. Ramsay, Hooker and Graves (2009) Functional Data Analysis with. R ...

Functional Data Analysis using fda.usc package - RPubs

Regression models are those techniques for modeling and analyzing the relationship between a dependent variable and one or more independent ...

Functional Regression Analysis - Search R Project

Similarly, categorical independent variables with k k k levels are translated into k − 1 k-1 k−1 contrasts in xfdlist . Any smoothing information is passed to ...

Introduction to Functional Data Analysis with R - R Views

FDA is a branch of statistics that deals with data that can be conceptualized as a function of an underlying, continuous variable. The data in ...

Functional Data Analysis in R by fda.usc package

fds with functional data sets and rainbow for functional data display and outlier detection. refund allows computing functional penalized regression. Functional ...

an R package for functional principal component logit regression

... packages mainly in R for using functional data analysis (FDA) methods. Every package is designed from the point of view followed by its developer and the ...

Functional Data Analysis using fda.usc package - RPubs

GPFDA: Use Functional regression as the mean structure and Gaussian Process as the covariance structure. MFHD: Multivariate Functional Halfspace ...

fda: Functional Data Analysis

Functional Data Analysis with R and Matlab (Springer). The package includes data sets and script files working many examples including all but one of ...

Functional analysis in R with fda - Cross Validated - Stack Exchange

There are a few things going on here. I don't use the fda package, and highly software-specific questions are off topic here, ...

The R Package fda.usc - Journal of Statistical Software

usc also includes func- tions to compute functional regression models, with a scalar response and a functional explanatory data via non- ...

fda-package: Functional Data Analysis in R - rdrr.io

Functions and data sets companion to Ramsay, J. O.; Hooker, Giles; and Graves, Spencer (2010) Functional Data Analysis with R and Matlab, plus Ramsay, ...

Functional data analysis with the refund package - Psychoco

Functional data analysis. Splines refund. fMRI example. References. Why refund? The original R package fda (Ramsay et al., 2009) uses penalized splines to fit ...

Functional Data Analysis: Discrete Observations to ... - Matthew Parker

Since we will be working in R, we should install any packages that we will be using. Today we will be looking at the package fda : Hide Code.

fda package - RDocumentation

Functions in fda (6.2.0) ... Create smooth functions that fit scatterplot data. ... F-statistic for functional linear regression. ... Permutation F- ...

predict.fRegress: Predict method for Functional Regression in fda

References. Ramsay, James O., Hooker, Giles, and Graves, Spencer (2009), Functional data analysis with R and Matlab, Springer, ...

Statfda. Functional data analysis with R

Choose the functional data analysis methodology that best suits your objective among the ones proposed (exploratory analysis, dimension reduction, linear fit ...

Statistical Computing in Functional Data Analysis: The R Package ...

The R package fda.usc also includes functions to compute functional regression models, with a scalar response and a functional explanatory data ...

fda: Functional Data Analysis - James Ramsay

New York: Springer and in Ramsay, J. O., Hooker, Giles, and Graves, Spencer (2009). Functional Data Analysis with R and Matlab (Springer). The package includes ...

Resources - Functional Data Analysis Lab - NC State

Contains functions to conduct function-on-scalar regression, penalized functional regression, functional principal components analysis (sparse or dense data), ...

fda.usc-package function - RDocumentation

This devel version carries out exploratory and descriptive analysis of functional data exploring its most important features: such as depth measurements or ...