The data at both ends of the plot tracks the fitted curve. The confidence bounds are closer together indicating that there is less uncertainty in prediction. This graph shows a much better fit to the data. Then, drag the vertical reference line to the x-value of 2 (or type 2 in the X Values text box). In the Degree box at the top, type 3 for a cubic model. The two points to the right are dragging down the estimate of the slope. The bulk of the data with x-values between zero and two has a steeper slope than the fitted line. If you do not specify the degree of the polynomial, polytool does a linear fit to the data. The variables x1 and y1 are data points from the "true" function without error. The variables x and y are observations made with error from a cubic polynomial. The second step is to use Fubini's theorem to reverse the order in which X and D are integrated out. The first step is to recognize that E X, E X E, since X and E are independent. To start the demonstration, you must first load the data set. To compute the expected test error analytically, we rewrite the expectation operators in two steps. You can use polytool to do curve fitting and prediction for any set of x-y data, but, for the sake of demonstration, the Statistics Toolbox provides a data set ( polydata.mat) to teach some basic concepts. An Export list box to store fit results into variables.A Close button to end the demonstration.Bounds and Method menus to control the confidence bounds and choose between least squares or robust fitting.A draggable vertical reference line to do interactive evaluation of the polynomial at varying x-values.A data entry box to evaluate the polynomial at a specific x-value.A data entry box to change the degree of the polynomial fit.y-axis text to display the predicted y-value and its uncertainty at the current x-value.A graph of the data, the fitted polynomial, and global confidence bounds on a new predicted value.Y polyval(p,X) returns the predicted value of a polynomial given. The polytool demo has the following features: Y polyval(p,X) Y,DELTA polyval(p,X,S) Description. ![]() The polytool demo is an interactive graphic environment for polynomial curve fitting and prediction. Demos (Statistics Toolbox) Statistics Toolbox
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |