Learn R Programming

berryFunctions (version 1.21.2)

exp4p: 4-parametric exponential function

Description

Fits an exponential function of the form a*e^(b*(x+c))+d

Usage

exp4p(x, y, digits = 2, plot = FALSE, las = 1, col = 1:6, legarg = NULL, ...)

Arguments

x, y

x and y Data

digits

significant digits for rounding R^2. DEFAULT: 2

plot

plot data and fitted functions? DEFAULT: FALSE

las

label axis style, see par. DEFAULT: 1

col

6 colors for lines and legend texts. DEFAULT: 1:6

legarg

Arguments passed to legend. DEFAULT: NULL

further graphical parameters passed to plot

Value

Data.frame with the 4 parameters for each optim method

Details

This is mainly a building block for mReg

See Also

mReg, lm

Examples

Run this code
# NOT RUN {
## Skip time consuming checks on CRAN
# exponential decline of temperature of a mug of hot chocolate
tfile <- system.file("extdata/Temp.txt", package="berryFunctions")
temp <- read.table(tfile, header=TRUE, dec=",")
head(temp)
plot(temp)
temp <- temp[-20,] # missing value - rmse would complain about it
x <- temp$Minuten
y <- temp$Temp
rm(tfile, temp)

exp4p(x,y, plot=TRUE)
# y=49*e^(-0.031*(x - 0  )) + 25 correct, judged from the model:
# Temp=T0 - Te *exp(k*t) + Te     with    T0=73.76,  Tend=26.21, k=-0.031
# optmethod="Nelder-Mead"  # y=52*e^(-0.031*(x + 3.4)) + 26 wrong
# }
# NOT RUN {
# }

Run the code above in your browser using DataLab