Filter löschen
Filter löschen

correlation and fitting line to a data set with standard error

3 Ansichten (letzte 30 Tage)
Dear friends,
suppose we have a set of data as
X=x1,x2,x3,x4,.......x26 , Y= y1+/-a , y2+/- b, y3+/-c ........, y26+/-z (a..z are standard error for each value of yi )
would you tell me 1- how can we find the correlation between X, Y, 2- how can we fit a line/curve to these data

Akzeptierte Antwort

Star Strider
Star Strider am 12 Nov. 2012
It's easy to convert the standard errors ( SE ) into inverse-variance weights:
Wgt = 1./(N.*SE.^2);
where N are the number of observations used to calculate each SE. They are usually the same for all but can vary, so this allows N to be a vector of the same size as SE.
1. This File Exchange routine calculates a Weighted Correlation Matrix.
2. Weighted Nonlinear Regression is easy enough to do (in 2012a and later). In 2011 and earlier versions, it is a bit more complicated but definitely possible. (See this Weighted Nonlinear Regression Demo for details.) If you want to do linear regression, all you have to do is specify a linear model.

Weitere Antworten (1)

karlo gonzales
karlo gonzales am 12 Nov. 2012
thank you so much "Star Strider" for your hints!

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by