Confidence intervals around trend

I am trying to compute confidence intervals around a trend line, such as that seen in the website below:

http://tidesandcurrents.noaa.gov/sltrends/sltrends_station.shtml?stnid=2695540%20Bermuda%20Esso%20Pier,%20BERMUDA

I am not confident that using polyconf with ployfit is the right way to go. Can anyone suggest how I might achieve this? Many thanks

Answer 1

[Wayne King]

Do you have the Statistics Toolbox?

One way:

    load carsmall;
    X = ones(length(Horsepower),2);
    X(:,2) = Horsepower;
    Y = Acceleration;
    [b,bint] = regress(Y,X);
    x = min(Horsepower):0.01:max(Horsepower);
    yfit = b(1)+b(2)*x;
    plot(Horsepower,Y,'k*')
    hold on;
    ylower = bint(1,1)+ bint(2,1)*x;
    yupper = bint(1,2)+bint(2,2)*x;
    plot(x,yfit,'r','linewidth',2)
    plot(x,ylower,'b-.')
    plot(x,yupper,'b-.')

Another way using LinearModel.fit

   mdl = LinearModel.fit(Horsepower,Y);
   ci = coefCI(mdl);

Note that ci is the same matrix as bint. The nice thing about LinearModel.fit is that there is a plot() method that will give you the plot with the confidence intervals

plot(mdl)

Answer 2

[Shashank Prasanna]

You can use polyconf

Alternatively you can fit your model using LinearModel.fit and use predict to collect the second argument which is the prediction confidence interval.

Set the 'Prediction' to 'Curve' to predict confidence bounds for the fitted mean (trend) values.

Answer 3

[star]

I should say that before trying to compute the confidence interval, it is better if you try to figure out where does it come from? Then, you can calculate through any software. Software are just languages.