README

stanislav zamecnik

03 11 2021

OEFPIL

Optimal Estimation of Parameters by Iterated Linearization

The original version of this software was written in R by Stanislav Zámečník, Zdeňka Geršlová and Vojtěch Šindlář in year 2021. The package is based on theoretical background of work of prof. Gejza Wimmer and afterwards implemented by mentioned authors. Main features of the package include:

Installation

You can install the release version of package from CRAN:

install.packages("OEFPIL")

Or the development version from GitHub repository:

devtools::install_github("OEFPIL/OEFPIL")

Usage

In R session do:

library(MASS)
steamdata <- steam
colnames(steamdata) <- c("x","y")
k <- nrow(steamdata)
CM <- diag(rep(10,2*k))

Creating OEFPIL object which we want to work with

library(OEFPIL)
st1 <- OEFPIL(steamdata, y ~ b1 * 10 ^ (b2 * x/ (b3 + x)),
list(b1 = 5, b2 = 8, b3 = 200), CM, useNLS = FALSE)

Displaying results using summary function

summary(st1)
## Summary of the result:  
##  
## y ~ b1 * 10^(b2 * x/(b3 + x))
## 
##     Param Est         Std Dev   CI Bound 2.5 %   CI Bound 97.5 %
## b1   4.487870        1.526903         1.495196          7.480545
## b2   7.188155        1.865953         3.530953         10.845356
## b3 221.837783       99.953658        25.932214        417.743352
## 
##  Estimated covariance matrix: 
##            b1         b2        b3
## b1   2.331432   2.296195  134.3054
## b2   2.296195   3.481782  184.6313
## b3 134.305405 184.631318 9990.7337
## 
##  Number of iterations: 10

Plot of estimated function

plot(st1, signif.level = 0.05, interval = "conf", main  = "Estimated function by iterated linearization")

Ggplot graph of estimated function

library(ggplot2)
curvplot.OEFPIL(st1, signif.level = 0.05)

For more information and examples see:

?OEFPIL

This software OEFPIL was financed by the Technology Agency of the Czech Republic within the ZETA Programme. https://www.tacr.cz .