qpcR_functions {qpcR} | R Documentation |
A summary of all available models implemented in this package.
l5 l4 l3 b5 b4 b3 w4 w3 baro5 expGrowth
The following nonlinear models are implemented:
l5:
f(x) = c + frac{d-c}{(1+exp(b(log(x)-log(e))))^f}
l4:
f(x) = c + frac{d-c}{1+exp(b(log(x)-log(e)))}
l3:
f(x) = frac{d}{1+exp(b(log(x)-log(e)))}
b5:
f(x) = c + frac{d-c}{(1+exp(b(x-e)))^f}
b4:
f(x) = c + frac{d-c}{1+exp(b(x-e))}
b3:
f(x) = frac{d}{1+exp(b(x-e))}
w4:
f(x) = c + (d-c) exp(-exp(b(log(x)-log(e))))
w3:
f(x) = d exp(-exp(b(log(x)-log(e))))
expGrowth:
f(x) = a * exp(b * x) + c
baro5:
f(x) = c + frac{d-c}{1+fexp(b1(log(x)-log(e))) + (1-f)exp(b2(log(x)-log(e)))}
with
f = frac{1}{1 + exp((2b1b2/|b1+b2|)(log(x)-log(e)))}
The functions are defined as a list containing the following items:
$expr
the function as an expression for the fitting procedure.
$fct
the function defined as f(x, parm)
.
$ssfct
the self-starter function.
$d1
the first derivative function.
$d2
the second derivative function.
$inv
the inverse function.
$expr.grad
the function as an expression for gradient calculation.
$inv.grad
the inverse functions as an expression for gradient calculation.
$parnames
the parameter names.
$name
the function name.
$type
the function type as a character string.
Andrej-Nikolai Spiess
m1 <- pcrfit(reps, 1, 2, b3) m2 <- pcrfit(reps, 1, 2, b5) m3 <- pcrfit(reps, 1, 2, w4) ## get the second derivative ## curve of m2 d2 <- b5$d2(m2$DATA[, 1], coef(m2)) plot(m2) lines(d2, col = 2)