Community Profile

Contact

Top 1% contributor

Hi Alice I just ran this same example using MATLAB and Excel. In both cases, the coefficients from the nonlinear regression ag...

accepted

3

Answered 4 years ago

92 downloads

4 years ago

Here's a pretty basic example X = linspace(0, 2*pi, 100); X = X'; Y = sin(X) + randn(100,1); foo = fit(X,Y, 's...

2

Answered 3 years ago

55 downloads

In general when I hear the expression parametric bootstrap I think "parametric residual bootstrap" I'm attaching some simple ...

1

Statistics Toolbox includes two different algorithms (nlmefit and nlmefitsa) for fitting nonlinear mixed effects model. nlmefit...

33 downloads

3 years ago

41 downloads

MathWorks tech support has a solution documenting various options for weighted regression. http://www.mathworks.com/support/s...

Automatically detecting outliers is tricky stuff. You normally need fairly precise information regarding your data as well as t...

MATLAB includes a wide variety of functions that can be used to simulate a random walk. Depending on what precisely you want to...

MATLAB and Statistics Toolbox provide a variety of ways to perform a regression. For example, if I am performing a simple linea...

I'm attaching code that shows a couple different ways to solve your problem. I prefer the second option. The R^2 is slightly...

I'm attaching some code that might provide helpful I also have a two part blog posting on this same subject that provides a b...

0

Local regression (aka LOWESS/LOESS) and interpolation don't lend themselves to parametric representations. There really isn't a...

For simplicity, this code is using a simple linear model. However, the same syntax with work for your nonlinear regression. ...

Here's a simple example using the new regression functions in the 12a release. All you need to do is pass the appropriate weigh...

Hi Miguel fitensemble is able to handle multiple independent variables. You should be able to use this with the data set tha...

The SVM implementation in Bioinformatics Toolbox is limited to binary classification. The Naive Bayes classifier in Statistic...

Hi George Conveniently, 12a also has a function call NonLinearModel %% Generate some data X = 2* pi*rand(100,1); ...

Curve Fitting Toolbox allows you to specify constraints for individual regression coefficients. With this said and done, coul...

Here's the rub... When you fit a second order Fourier series, you're estimating values for six different regression coefficie...

nlinfit in Statistics Toolbox # Uses Levenberg-Marquardt under the hood # Allows you to input a vector of weights See <ht...

Have you looked into the dataset array that ships with Statistics Toolbox? The dataset array is a special data type that can ...

Try the following X = linspace(1, 2*pi, 50); X = X'; Y = sin(X) + randn(50,1); foo = fit(X,Y, 'sin1'); ...

I'd strongly recommend that you look at a file exchange submission by John D'Errico titled "Shape Modeling Language" http://w...

Couple comments: Curve Fitting Toolbox includes a lot of nice code that will automatically choose "good" starting points for ...

If you need confidence intervals nlinfit is a better option

I'd strongly suggestion that you watch a webinar titled "Electricity Load and Price Forecasting with MATLAB". The webinar is av...

Offhand, I don't know any way to change the display within the tool itself. With this said and done, its fairly easy to 1. ...

Load more