This package is considered a duplicate. The official version of this package is found at:https://jihx1015.r-universe.dev/MECfda

Package: MECfda 0.1.0

Heyang Ji

MECfda: Scalar-on-Function Regression with Measurement Error Correction

Solve scalar-on-function linear models, including generalized linear mixed effect model and quantile linear regression model, and bias correction estimation methods due to measurement error. Details about the measurement error bias correction methods, see Luan et al. (2023) <doi:10.48550/arXiv.2305.12624>, Tekwe et al. (2022) <doi:10.1093/biostatistics/kxac017>, Zhang et al. (2023) <doi:10.5705/ss.202021.0246>, Tekwe et al. (2019) <doi:10.1002/sim.8179>.

Authors:Heyang Ji [aut, cre, ctb, dtc], Ufuk Beyaztas [ctb, rev], Nicolas Escobar-Velasquez [com], Yuanyuan Luan [ctb], Xiwei Chen [ctb], Mengli Zhang [ctb], Roger Zoh [ths], Lan Xue [ths], Carmen Tekwe [ths]

MECfda_0.1.0.tar.gz
MECfda_0.1.0.tar.gz(r-4.5-noble)MECfda_0.1.0.tar.gz(r-4.4-noble)
MECfda_0.1.0.tgz(r-4.4-emscripten)MECfda_0.1.0.tgz(r-4.3-emscripten)
MECfda.pdf |MECfda.html✨
MECfda/json (API)

# Install 'MECfda' in R:

install.packages('MECfda', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

MECfda.data.sim.0.0 - Simulated data
MECfda.data.sim.0.1 - Simulated data
MECfda.data.sim.0.2 - Simulated data
MECfda.data.sim.0.3 - Simulated data
MECfda.data.sim.1.0 - Simulated data
MECfda.data.sim.1.1 - Simulated data
MECfda.data.sim.1.2 - Simulated data
MECfda.data.sim.1.3 - Simulated data

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.00 score 1 stars 1 scripts 127 downloads 19 exports 67 dependencies

Last updated 2 months agofrom:049a325981. Checks:OK: 2. Indexed: no.

Target	Result	Date
Doc / Vignettes	OK	Dec 21 2024
R-4.5-linux	OK	Dec 21 2024

Exports:%>%basis2fun bspline_basis bspline_basis_expansion bspline_series bsplineSeries2fun extractCoef fc.beta fcQR fcRegression fourier_basis_expansion Fourier_series FourierSeries2fun functional_variable ME.fcLR_IV ME.fcQR_CLS ME.fcQR_IV.SIMEX ME.fcRegression_MEM plot

Dependencies:ash bitops boot cli cluster colorspace corpcor deSolve dplyr fansi farver fda fds FNN generics ggplot2 glme glue gss gtable hdrcde isoband kernlab KernSmooth ks labeling lattice lifecycle lme4 locfit magrittr MASS Matrix MatrixModels mclust mgcv minqa multicool munsell mvtnorm nlme nloptr pcaPP pillar pkgconfig plyr pracma quantreg R6 rainbow RColorBrewer Rcpp RcppEigen RCurl reshape rlang scales SparseM stringi stringr survival tibble tidyselect utf8 vctrs viridisLite withr

MECfda: An R package for bias correction due to measurement error in functional and scalar covariates in scalar-on-function regression models

Ji, Heyang, Beyaztas, Ufuk, Escobar, Nicolas, Luan, Yuanyuan, Chen, Xiwei, Zhang, Mengli, Zoh, Roger, Xue, Lan, Tekwe, Carmen

Rendered fromMECfda.Rmdusingknitr::rmarkdownon Dec 21 2024.

Last update: 2024-10-21
Started: 2024-10-21

Citation

Readme and manuals

Help Manual

Help page	Topics
From the summation series of a functional basis to function value	basis2fun basis2fun,bspline_series,numeric-method basis2fun,Fourier_series,numeric-method
B-splines basis expansion for functional variable data	bspline_basis_expansion bspline_basis_expansion,functional_variable,integer-method
b-spline basis	bspline_basis bspline_basis-class
b-splines summation series.	bspline_series bspline_series-class
Compute the value of the Fourier summation series at certain points.	bsplineSeries2fun bsplineSeries2fun,bspline_series,numeric-method
Extract dimensionality of functional data.	dim,functional_variable-method
Method of class Fourier_series to extract Fourier coefficients	extractCoef extractCoef,Fourier_series-method
Extract the value of coefficient parameter function	fc.beta fc.beta,fcQR-method fc.beta,fcRegression-method
Solve quantile regression models with functional covariate(s).	fcQR
Solve linear models with functional covariate(s)	fcRegression
Fourier basis expansion for functional variable data	fourier_basis_expansion fourier_basis_expansion,functional_variable,integer-method
s4 class of Fourier summation series	Fourier_series Fourier_series-class
Compute the value of the Fourier summation series	FourierSeries2fun FourierSeries2fun,Fourier_series,numeric-method
Function-valued variable data.	functional_variable functional_variable-class
Bias correction method of applying linear regression to one functional covariate with measurement error using instrumental variable.	ME.fcLR_IV
Bias correction method of applying quantile linear regression to dataset with one functional covariate with measurement error using corrected loss score method.	ME.fcQR_CLS
Bias correction method of applying quantile linear regression to dataset with one functional covariate with measurement error using instrumental variable.	ME.fcQR_IV.SIMEX
Use UP_MEM or MP_MEM substitution to apply (generalized) linear regression with one functional covariate with measurement error.	ME.fcRegression_MEM
Simulated data	MECfda.data.sim.0.0
Simulated data	MECfda.data.sim.0.1
Simulated data	MECfda.data.sim.0.2
Simulated data	MECfda.data.sim.0.3
Simulated data	MECfda.data.sim.1.0
Simulated data	MECfda.data.sim.1.1
Simulated data	MECfda.data.sim.1.2
Simulated data	MECfda.data.sim.1.3
Plot b-splines baisi summation series.	plot,bspline_series-method
Plot Fourier basis summation series.	plot,Fourier_series-method
Predicted values based on fcQR object	predict.fcQR
Predicted values based on fcRegression object	predict.fcRegression