Is this good practice. I suggest the following: 1) As you receive help, try to give it too, by answering questions in your area of expertise. 2) Read the faq! 3) When you see good This is in part because of the great ability of the human visual system to be an intuitive integrator. Why are so many metros underground?

In it, you'll get: The week's top questions and answers Important community announcements Questions that need answers see an example newsletter By subscribing, you agree to the privacy policy and terms Legal Site Map WolframAlpha.com WolframCloud.com Enable JavaScript to interact with content and submit forms on Wolfram websites. Making sense of U.S. Note also that because all four quadrants of the plot of the data and the fit contain significant amounts of data, FindFit displays the plot of the residuals separately.

The fourth line of the progress report tells us that the method has been changed. Near Earth vs Newtonian gravitational potential Is accuracy binary? And when you get close to the bottom of the valley you will want to start taking baby steps. The total number of counts in the data, peak plus background, can be calculated.

Of course, if you take giant steps you might step over the next hill and end up in the wrong valley. As an example, we generate some made-up data for three peaks with a Lorentzian shape using the Lorentzian function supplied with the EDA`FindFit` package. Not the answer you're looking for? NonlinearModelFit[{{x11,x12,…,y1},{x21,x22,…,y2},…},form,{β1,…},{x1,…}]constructs a nonlinear model where form depends on the variables xk.

FindFit can use other methods, controlled with a Method option. Services Technical Services Corporate Consulting For Customers Online Store Product Registration Product Downloads Service Plans Benefits Support Support FAQ Customer Service Contact Support Learning Wolfram Language Documentation Wolfram Language Introductory Book Any suggestions and related material would be appreciated! This situation leads to ambiguity about which fit results are "correct." 5.1.2 Providing Initial Parameter Values to FindFit As already mentioned, unless we are fitting to a very simple model, FindFit

This is because for many nonlinear fits, sorting out how to combine the various error terms is problematic. In[3]:= Out[3]= Now we reweight the data. Try Needs["ErrorBarPlots`"] –Jinxed Mar 17 '15 at 13:45 Look up "error bars" on this site and in Mathematica's documentation. Is this good practice.

If those answers do not fully address your question, please ask a new question. Questions on problems in code must describe the specific problem and include valid code to reproduce it. Many hits. –Sjoerd C. Further, many of the fitted parameters are zero within calculated errors.

Teukolsky, and William T. In[27]:= Out[27]= ToFitFunction is similar to the ToLinearFunction function supplied in the EDA`LinearFit` package, but somewhat more general. I was playing around with the NMinimize options "NelderMead", "RandomSearch", "SimulatedAnnealing" and "DifferentialEvolution", but up to this point none of them was able to reproduce the fit obtained by ignoring the How much interest should I pay on a loan from a friend?

Note that in comparison to fits you may have done using LinearFit, FindFit is very slow. A Shadowy Encounter Developing web applications for long lifespan (20+ years) How should I interpret "English is poor" review when I used a language check service before submission? The model can be linearized as follows. de Vries, Yves KlettIf this question can be reworded to fit the rules in the help center, please edit the question.

In[9]:= Out[9]= Note that the Reweight option, which is True by default for LinearFit, is False by default for FindFit. The error on the first points are gigantic so it just ignores them... –chris May 22 '13 at 9:04 It also occurs with smaller errors. Valid values include Gradient, Newton, and QuasiNewton, all of which are passed to FindMinimum. Please try the request again.

Chem. 66 (1994), p. 23. We can access the covariance matrix of the estimated parameters using nlm["CovarianceMatrix"] yielding {{0.00945806, -0.00530171}, {-0.00530171, 0.00307167}} share|improve this answer answered Mar 16 '13 at 23:58 joshsilverman 1725 add a comment| Buydens, G. Related 2Using NonlinearModelFit to fit data with errors1Function optimization errors11Fitting Vogel's formula for phyllotaxis to the image of a flower-1How to fit one parametric array to another numerical array?0Getting standard errors

In[20]:= Out[20]= If ResidualPlacement is set to None, no residual plot is displayed. Not only is the fit very sensitive to the initial values, but on a very fast Linux machine running a 500 Mhz Xeon processor the fit took over 15 seconds of Similarly, when there are explicit errors in the data, we form the chi-squared, , and we solve the corresponding equations. However, we can see the peak and probably make some sensible guesses of its parameters.

In[25]:= We fit this transformed data to a straight line. If there are declared errors in the data being fit, so that the test is comparing chi-squared statistics, the default value of 0.1 for this option is usually reasonable. A classic introduction to nonlinear fitting techniques Xiang Ouyang and Philip L. First we fit Cobalt60Data to a Gaussian plus linear background without reweighting; we also suppress the graphs of the fit by using the ShowFit option.

Not the answer you're looking for? In[7]:= Out[7]= From the plot of the data we estimate the center of the peak to be at channel 1830, and the amplitude above the background is about 140 counts. Using the Datum construct, we can find the counts and error in the counts due to the background. In[21]:= Out[21]= Internally, ShowFitResult uses EDAListPlot, Plot, and ToFitFunction.

The full width at half-maximum is about 90 channels, so we will try an initial value for sigma of 45 channels. prof. assist. Thus, we form a data set of {ipscTau, Log[frequency]}.