Curve Fitting Toolbox™

fittype - Constructor for fittype object

Syntax

ffun = fittype(libname)
ffun = fittype(expr)
ffun = fittype({expr1,...,exprn})
ffun = fittype(expr,PropName,PropVal,...)
ffun = fittype({expr1,...,exprn},PropName,PropVal,...)

Description

ffun = fittype(libname) constructs the fittype object ffun for the library model specified by libname. You can display library model names with the cflibhelp function.

ffun = fittype(expr) constructs the fittype object ffun for the custom nonlinear model specified by the expression in the string expr. By default, the independent variable is assumed to be x and the dependent variable is assumed to be y. All other variables are assumed to be coefficients. All coefficients must be scalars.

Note   The following coefficient names are not allowed in the expression string expr: i, j, pi, inf, nan, eps.

ffun = fittype({expr1,...,exprn}) constructs the fittype object ffun for the custom linear model with terms specified by the expressions in the strings expr1, expr2, ... , exprn. Coefficients are not included in the expressions for the terms. If there is a constant term, use '1' as the corresponding expression in the cell array.

Note   islinear assumes that all models specified with the syntax ffun = fittype(expr) are nonlinear models. To create a linear model with fittype that will be recognized as linear by islinear (and, importantly, by the algorithms of fit), use the syntax ffun = fittype({expr1,...,exprn}).

ffun = fittype(expr,PropName,PropVal,...) or ffun = fittype({expr1,...,exprn},PropName,PropVal,...) constructs the fittype object ffun using specified property name/value pairs. Supported property names and values are given in the table below.

Example

Construct a fittype object for the rat33 library model:

f = fittype('rat33')
f =
   General model Rat33:
   f(p1,p2,p3,p4,q1,q2,q3,x) = 
         (p1*x^3 + p2*x^2 + p3*x + p4)/
                (x^3 + q1*x^2 + q2*x + q3)

Construct a fittype object for a custom nonlinear model, designating n as a problem-dependent parameter and u as the independent variable:

g = fittype('a*u+b*exp(n*u)',...
            'problem','n',...
            'independent','u')
g =
     General model:
       g(a,b,n,u) = a*u+b*exp(n*u)

Construct a fittype object for a custom linear model, specifying the names of the coefficients:

h = fittype({'cos(x)','1'},'coefficients',{'a1','a2'})
h =
     Linear model:
       h(a1,a2,x) = a1*cos(x) + a2

See Also

fit, cfit

fitoptions

formula