Gauss1 {NISTnls} | R Documentation |
The Gauss1
data frame has 250 rows and 2 columns of generated data.
y |
A numeric vector of generated responses. |
x |
A numeric vector of generated input values. |
This data frame contains the following columns:
The data are generated data with two well-separated Gaussians on a decaying exponential baseline plus normally distributed zero-mean noise with variance = 6.25.
Rust, B., NIST (1996).
library(NISTnls) data(Gauss1) plot(y ~ x, data = Gauss1) fm1 <- nls(y ~ b1*exp( -b2*x ) + b3*exp( -(x-b4)**2 / b5**2 ) + b6*exp( -(x-b7)**2 / b8**2 ), data = Gauss1, trace = TRUE, start = c(b1 = 97.0, b2 = 0.009, b3 = 100.0, b4 = 65.0, b5 = 20.0, b6 = 70.0, b7 = 178., b8 = 16.5)) fm2 <- nls(y ~ b1*exp( -b2*x ) + b3*exp( -(x-b4)**2 / b5**2 ) + b6*exp( -(x-b7)**2 / b8**2 ), data = Gauss1, trace = TRUE, start = c(b1 = 94.0, b2 = 0.0105, b3 = 99.0, b4 = 63.0, b5 = 25.0, b6 = 71.0, b7 = 180.0, b8 = 20.0)) fm3 <- nls(y ~ cbind(exp(-b2*x), exp(-(x-b4)**2/b5**2), exp(-(x-b7)**2/b8**2)), data = Gauss1, trace = TRUE, start = c( b2 = 0.009, b4 = 65.0, b5 = 20.0, b7 = 178., b8 = 16.5), algorithm = "plinear") fm4 <- nls(y ~ cbind(exp(-b2*x), exp(-(x-b4)**2/b5**2), exp(-(x-b7)**2/b8**2)), data = Gauss1, trace = TRUE, start = c( b2 = 0.0105, b4 = 63.0, b5 = 25.0, b7 = 180., b8 = 20.0), algorithm = "plinear")