[Content_Types].xml
_rels/.rels
matlab/_rels/document.xml.rels
matlab/document.xml
matlab/output.xml
media/image1.png
media/image2.png
metadata/coreProperties.xml
metadata/mwcoreProperties.xml
metadata/mwcorePropertiesExtension.xml
metadata/mwcorePropertiesReleaseInfo.xml
MATLAB Least Squares Regression In this livescript, you will learn how To perform least squares regression using inbuilt MATLAB functions. Consider the data set x = [0.6939 2.0925 3.3455 4.1205 4.8542 6.1242 6.9356 8.3777 8.8859 10.1363];
y = [3.7744 8.0446 16.9718 23.9429 32.5361 52.6056 60.2304 81.6795 94.6263 115.0161]; To perform a regression analysis, it’s typically a good idea to plot the data on a scatter plot to get an idea of what it looks like plot(x,y,’.’,’MarkerSize’,15) From the looks of it, the data seems quite linear, so let’s begin by fitting a linear model. Graphical Curve Fitting The simpliest way of we can use the ‘Basic Fitting’ toolbox. To do this, we first plot the data as usual. figure(‘Visible’,”on”)
plot(x,y,’.’,’MarkerSize’,15) To use the toolbox, you need to navigate to the tools menu, then the Basic Fitting tab. (a) Using the Basic Fitting toolbox, fit a linear curve to the data provided. For more advanced curvefitting, we can call the Curve Fitting Toolbox from the command line using \texttt{cftool} . (b) Use \texttt{cftool} to fit a linear curve to the \texttt{x} and \texttt{y} . Curve fitting from the command window In MATLAB, there are a number of ways to do this, the easiest begin \texttt{fitlm} which takes the \texttt{x} and \texttt{y} values as inputs and outputs the parameters for a linear model. fitlm(x,y) (c) Run this command. The outputs are quite convoluted, with many statistical measures, but it is good for more advanced analyses. If you know the form of the model, it is also possible to conduct a fit from the command line. The function \texttt{polyfit(xval,yval,n)} is great for polynomial fitting. It takes inputs in the form of the \texttt{x} and \texttt{y} values, in addition to the order ( n ) of the polynomial that we’d like to use. a = polyfit(x,y,1) (d) Run this command. NOTE : If we specify n as the p-1 , where p is the number of points in our data set, \texttt{polyfit} provides the interpolating polynomial of order p-1 . You would have noticed that the function outputs a vector of two values. These are infact the coefficients of the linear function y=a_{1}x+a_{0} And we can evaluate this function using \texttt{polyval} . We just have to provide an input of the polynomial coefficients and a point, say x=5.5 . polyval(a,5.5) (e) Run this command. For more general fitting, MATLAB has the function \texttt{fit(x,y,fitType)} . It takes the column vectors \texttt{x} and \texttt{y} , and a model to fit this data against. These include: ‘poly1’ Linear polynomial curve ‘poly2’ Quadratic polynomial curve ‘linearinterp’ Piecewise linear interpolation ‘cubicinterp’ Piecewise cubic interpolation ‘smoothingspline’ Smoothing spline (curve) ‘lowess’ Local linear regression (surface) So for our model, we have fit(x’,y’,’poly1′) (f) Run this command and see if it gives the same predictions as before. If you want more general functions, you can specify these inside \texttt{fit} . For example, if we wanted to fit a power function of the form y=ax^{b} then we can run the command fit(x’,y’,’a*x^b’) (g) Run this command
manual code ready 0.4 figure 88dbb45d-f178-4fd0-8789-e668ec814690 data:image/png;base64,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 560 420 2 2 3 figure 9f6aa3df-b65b-4d7e-813c-88e0a1f46742 data:image/png;base64,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 560 420 4 5 4 4 5 matrix a 1×2 1 2 double 12.2362 -19.0490
double double [[{“value”:”{\”value\”:\”12.2362\”}”},{“value”:”{\”value\”:\”-19.0490\”}”}]] 7 variable ans 48.2498 1 1 8 variableString ans Linear model Poly1:
ans(x) = p1*x + p2
Coefficients (with 95% confidence bounds):
p1 = 12.24 (10.23, 14.25)
p2 = -19.05 (-31.66, -6.435) false false 1 1 9 warning Warning: Start point not provided, choosing random start point. 10 variableString ans General model:
ans(x) = a*x^b
Coefficients (with 95% confidence bounds):
a = 2.313 (1.815, 2.811)
b = 1.689 (1.588, 1.789) false false 1 1 10 true false x = [0.6939 2.0925 3.3455 4.1205 4.8542 6.1242 6.9356 8.3777 8.8859 10.1363]; 0 6 6 false true y = [3.7744 8.0446 16.9718 23.9429 32.5361 52.6056 60.2304 81.6795 94.6263 115.0161]; 1 7 7 true true plot(x,y,’.’,’MarkerSize’,15) 2 10 10 0 true true fitlm(x,y) 3 12 12 true false figure(‘Visible’,”on”) 4 17 17 1 false true plot(x,y,’.’,’MarkerSize’,15) 5 18 18 1 true true cftool 6 23 23 true true a = polyfit(x,y,1) 7 35 35 2 true false polyval(a,5.5) 8 43 43 3 false true plot(log10(x(2:end)),log10(y(2:end)),’.’,’MarkerSize’,15) 9 44 44 true true fit(x’,y’,’poly1′) 10 50 50 4 true true fit(x’,y’,’a*x^b’) 11 57 57 5 6
2020-03-28T11:21:59Z 2020-03-31T13:18:18Z
application/vnd.mathworks.matlab.code MATLAB Code R2019b
9.7.0.1183724 b72b7423-3765-4965-94e0-6f9eefc6fd3f
9.7.0.1296695
R2019b
Update 4
Jan 20 2020
3546228467