R Under development (unstable) (2024-10-17 r87242 ucrt) -- "Unsuffered Consequences" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > # This file is part of the standard setup for testthat. > # It is recommended that you do not modify it. > # > # Where should you do additional test configuration? > # Learn more about the roles of various files in: > # * https://r-pkgs.org/tests.html > # * https://testthat.r-lib.org/reference/test_package.html#special-files > > library(testthat) > library(deFit) > > test_check("deFit") Program will fit the data with a univariate second-order differential equation. The differential equation is: x(2) = beta1 * x + beta2 * x(1) Optimizing... Finishing optimization... Estimating R_squared Estimating RMSE Estimating Hessian Program will fit the data with a bivariate first-order differential equation. The differential equations are: dx/dt = beta1 * x + beta2 * y dy/dt = beta3 * x + beta4 * y Optimizing... Finishing optimization... Estimating R_squared Estimating RMSE Estimating Hessian Program will fit the data with a bivariate first-order differential equation. The differential equations are: dx/dt = beta1 * x + beta2 * y dy/dt = beta3 * x + beta4 * y Optimizing... Finishing optimization... Estimating R_squared Estimating RMSE Estimating Hessian Program will fit the data with multilevel univariate second-order differential equation. The multilevel differential equations are: X(2) = (beta1 + etaI1) * X + (beta2 + etaI2) * X(1) Optimizing... Estimating random effects 2015 Estimating random effects 2016 Estimating random effects 2017 Estimating random effects 2018 Estimating R_squared Estimating RMSE Estimating Hessian Program will fit the data with multilevel univariate second-order differential equation. The multilevel differential equations are: X(2) = (beta1 + etaI1) * X + (beta2 + etaI2) * X(1) Optimizing... Estimating random effects 2015 Estimating random effects 2016 Estimating random effects 2017 Estimating random effects 2018 Estimating R_squared Estimating RMSE Estimating Hessian Program will fit the data with multilevel univariate second-order differential equation. The multilevel differential equations are: X(2) = (beta1 + etaI1) * X + (beta2 + etaI2) * X(1) Optimizing... Estimating random effects 2015 Estimating random effects 2016 Estimating random effects 2017 Estimating random effects 2018 Estimating R_squared Estimating RMSE Estimating Hessian PlottingProgram will fit the data with multilevel univariate second-order differential equation. The multilevel differential equations are: X(2) = (beta1 + etaI1) * X + (beta2 + etaI2) * X(1) Optimizing... Estimating random effects 2015 Estimating random effects 2016 Estimating random effects 2017 Estimating random effects 2018 Estimating R_squared Estimating RMSE Estimating Hessian Plotting[ FAIL 0 | WARN 0 | SKIP 0 | PASS 7 ] > > proc.time() user system elapsed 116.57 4.03 121.03