Updated!
"MH"<-function(field,diameter,mu=10e-7,sig=0.1,Ms=100,chi=0){
#variables mu, sig, chi, Ms
#input: field and diameter
#all in CGS
rho <- 5
kb <- 1.38e-16
t <- 300
length.d<-length(diameter)
length.H<-length(field)
M<-double(length.H)
for (i in 1:length.H){
S
Oops I forgot to add another line to the code (see below)!! You could add
some noise if you want to. Generating the data from the function was merely
a way to test if the fitting procedure works - I have experimental data that
should allow me to calculate the parameters mu, sig, chi and Ms based
Hi,
I have a function that generates a set of data but I am having problems
determining the parameters using the nls fitting procedure.
"MH"<-function(field,diameter,mu=10e-7,sig=0.1,Ms=100,chi=0){
#variables mu, sig, chi, Ms
#input: field and diameter
#all in CGS
rho <- 5
kb <- 1.38e-16
I've run into a problem with a fitting procedure I would like R to solve for
me. Basically I have to fit some data to an equation which includes a sum
within the formula e.g.
Y(x;a,b,c) = f_i(x;a,b,c_i) + m*x
where a,b are unknown and f_i(x) is the sum of another function over a known
interval i
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