Gauss2 {NISTnls} | R Documentation |
The Gauss2
data frame has 250 rows and 2 columns giving
y |
A numeric vector of generated response values. |
x |
A numeric vector of generated input values. |
This data frame contains the following columns:
The data are two slightly-blended Gaussians on a decaying exponential baseline plus normally distributed zero-mean noise with variance = 6.25.
Rust, B., NIST (1996)
library(NISTnls) data(Gauss2) plot(y ~ x, data = Gauss2) fm1 <- nls(y ~ b1*exp( -b2*x ) + b3*exp( -(x-b4)**2 / b5**2 ) + b6*exp( -(x-b7)**2 / b8**2 ), data = Gauss2, trace = TRUE, start = c(b1 = 96, b2 = 0.009, b3 = 103, b4 = 106, b5 = 18, b6 = 72, b7 = 151, b8 = 18)) fm2 <- nls(y ~ b1*exp( -b2*x ) + b3*exp( -(x-b4)**2 / b5**2 ) + b6*exp( -(x-b7)**2 / b8**2 ), data = Gauss2, trace = TRUE, start = c(b1 = 98, b2 = 0.0105, b3 = 103, b4 = 105, b5 = 20, b6 = 73, b7 = 150, b8 = 20)) fm3 <- nls(y ~ cbind(exp(-b2*x), exp(-(x-b4)**2/b5**2), exp(-(x-b7)**2/b8**2)), data = Gauss2, trace = TRUE, start = c(b2 = 0.009, b4 = 106, b5 = 18, b7 = 151, b8 = 18), algorithm = "plinear") fm4 <- nls(y ~ cbind(exp(-b2*x), exp(-(x-b4)**2/b5**2), exp(-(x-b7)**2/b8**2)), data = Gauss2, trace = TRUE, start = c(b2 = 0.0105, b4 = 105, b5 = 20, b7 = 150, b8 = 20), algorithm = "plinear")