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slim (version 0.1.1)

Singular Linear Models for Longitudinal Data

Description

Fits singular linear models to longitudinal data. Singular linear models are useful when the number, or timing, of longitudinal observations may be informative about the observations themselves. They are described in Farewell (2010) , and are extensions of the linear increments model to general longitudinal data.

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Version

Install

install.packages('slim')

Monthly Downloads

184

Version

0.1.1

License

GPL-3

Maintainer

Daniel Farewell

Last Published

May 15th, 2017

Functions in slim (0.1.1)

fit_slim

Fitter Function for Singular Linear Models
fitted.slim

Extract Model Fitted Values from Singular Linear Model
confint.slim

Confidence Intervals for Model Parameters from Singular Linear Model
dialysis

Renal Function in Three Groups of Peritoneal Dialysis Patients
print.slim

Print 'slim' Objects
residuals.slim

Extract Model Residuals from Singular Linear Model
vcov.slim

Extract Variance-Covariance Matrix from a 'slim' Object
coef.slim

Extract Model Coefficients from Singular Linear Model
compute_laurent

Laurent Expansion of Inverse of Linear Matrix Function
slim.methods

Methods for Singular Linear Model Fits
summary.slim

Summarizing Singular Linear Model Fits
list_covariances

List Covariance Matrices for Every Subject
predict.slim

Model Predictions from Singular Linear Model
slim-package

Singular linear models for longitudinal data.
slim

Fit Singular Linear Models