All Forums  Origin Forum  Origin Forum  advanced(?) data masking options for sigmoidialfit

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Screensize: 640 x 480 800 x 600 1024 x 768 1280 x 1024 UserName: Password: Anti-Spam Code: Format Mode: Basic  Help  Prompt  Format: Font Andale Mono Arial Arial Black Book Antiqua Century Gothic Comic Sans MS Courier New Georgia Impact Lucida Console Script MT Bold Stencil Tahoma Times New Roman Trebuchet MS Verdana   Size 1 2 3 4 5 6   Color Black Red Yellow Pink Green Orange Purple Blue Beige Brown Teal Navy Maroon LimeGreen Message: * HTML is OFF * Forum Code is ON Smilies [quote][i]Originally posted by suras[/i] [br]Hi, First: I am a newbie on Origin. I tried to find answers for my questions on the forum but without luck. However since I am new to this, it is likely already described but i just dont know the right terms to use for the search... Sorry if that is the case. Anyway; my question General problem: to do intelligent masking of data before fitting. I am analyzing multiple (96 as minimum, sometimes over 1000) sigmoidial curves. To get good precision fits with low and well behaved residuals its crucial that the all the data points that's not a part of the transition are masked. The values for this (the points that needs to be masked) is not global, so the masking has to be done for each curve to be fitted individually. This is what I want to learn how to do. So i need guidance in how to approach this in the most intelligent way. In the most simple case, with just one well defined transition, just normalizing the dataset and going with max and min can be "ok" but not more. But on several occasions i have more complex data to fit with multiple transitions or a lot of noise. I guess this is a problem for most sigmoidial fitting? Thanks in advance /S [/quote]   Check here to include your profile signature. Check here to subscribe to this topic.