SSl4cons: Self-Starting Nls 4 parameters logistic constraint regression...

Description Usage Arguments Format Value Examples

Description

This selfStart model evaluates the 4 parameters logistic regression model and its gradient. It has an initial attribute that will evaluate initial estimates of the parameters hAsym, Slope and xMid for a given set of data. Instead of the standard exp function this implementation use the 10^ function.

f(x)=lAsym +\frac{hAsym-lAsym}{1+10^{Slope(x-xMid)}}

Usage

1
SSl4cons(..constraint.value, x, Slope, hAsym, xMid)

Arguments

..constraint.value

a numeric value representing the lower asymptote when x trend to -Inf. In this function this value is not a parameter is just a numeric value to constraint lAsym parameter.

x

a numeric vector of values at which to evaluate the model

Slope

a numeric parameter representing the -slope of the function at the inflection point

hAsym

a numeric parameter representing the higher asymptote when x trend to Inf

xMid

is the x value corresponding to the inflection point

Format

A selfStart model

Value

The value returned is a list containing the nonlinear function, the self starter function and the parameter names.

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
# Load data
data(ecdata)
data(mfidata)

# Select analyte FGF for plate 1
dat <- mfidata[mfidata$plate=="plate_1" & mfidata$analyte=="FGF",]

sdf <- data_selection(dat, ecdata)[[1]]

cons <- scluminex("plate_1",sdf$standard, sdf$background,
           lfct="SSl4",
           bkg="constraint",
           fmfi="mfi",
           verbose=FALSE)

summary(cons)

# Comparison constraint vs no constraint (same returning value but
# estimate 3 parameters).
lAsym <- 1
Slope <- 2
hAsym   <- 2
xMid <- 3
concentration <- 2
SSl4(concentration, Slope, lAsym, hAsym, xMid)
SSl4cons(lAsym, concentration, Slope, hAsym, xMid)

drLumi documentation built on May 30, 2017, 5:47 a.m.