Curve Fitting Toolbox

excludedata

Specify data to be excluded from a fit

Syntax

• outliers = excludedata(xdata,ydata,'MethodName',MethodValue)
  

Arguments

xdata	A column vector of predictor data.
ydata	A column vector of response data.
'MethodName'	The data exclusion method.
MethodValue	The value associated with MethodName.
outliers	A logical vector that defines data to be excluded from a fit.

Description

outliers = excludedata(xdata,ydata,'MethodName',MethodValue) identifies data to be excluded from a fit using the specified MethodName and MethodValue. outliers is a logical vector containing 1's marking data points to exclude while fitting, and 0's marking data points to include while fitting. The data exclusion methods are given below.

Method	Description
box	A four-element vector that specifies a box of data to include in a fit. Data outside the box is excluded. You specify the box as [xmin xmax ymin ymax].
domain	A two-element vector that specifies the domain of data to include in a fit. Data outside this domain is excluded. You specify the domain as [xmin xmax].
indices	A vector specifying the indices of the data points to be excluded.
range	A two-element vector that specifies the range of data to include in a fit. Data outside this range is excluded. You specify the range as [ymin ymax].

Remarks

You can combine data exclusion methods using logical operators. For example, to combine methods using the | (OR) operator

• outliers = excludedata(xdata,ydata,'indices',[3 5]);
  outliers = outliers|excludedata(xdata,ydata,'box',[1 10 0 90]);
  

In some cases, you might want to use the ~ (NOT) operator to specify a box that contains all the data to exclude.

• outliers = ~excludedata(xdata,ydata,'box',[1 10 0 90]);
  

Example

Generate random data in the interval [0, 15], create a sine wave with noise, and add two outliers with the value 2.

• rand('state',0);
  x = 15*rand(150,1); 
  y = sin(x) + (rand(size(x))-0.5)*0.5;
  y(ceil(length(x)*rand(2,1))) = 2;
  

Identify outliers that are outside the interval [-1.5, 1.5] using the range method.

• outliers = excludedata(x,y,'range',[-1.5 1.5]);
  

Identify the same outliers using the indices method.

• ind = find((y>1.5)|(y<-1.5));
  outliers = excludedata(x,y,'indices',ind);
  

You can pass outliers to the fit function to exclude the specified data points from a fit.

• ftype = fittype('a*sin(b*x)');
  fresult = fit(x,y,ftype,'startpoint',[1 1],'exclude',outliers);
  

See Also

fit

disp

feval