Recent content by MarcJ

  1. MarcJ

    A Least-squares - fitting an inverse function

    I have cleaned up the Python code and created some plots for the values of ##a##, ##b## and ##c## mentioned above. Noise is simply added to the 'ideal' data, has a mean of 0 and a standard deviation of 0, 1 and 10. What I infer is that, at higher noise levels, the mean of the residual is...
  2. MarcJ

    A Least-squares - fitting an inverse function

    I'm getting closer, but we're not there yet. Let me first reply to your thoughts. We don't know the exact distance ##d## in the system, but we can make a well-defined move (##\Delta d##). That's what I meant when I said we don't know our starting point on the curve. So we need ##b## to account...
  3. MarcJ

    A Least-squares - fitting an inverse function

    Thanks Doctor! Thing is, I'm not using Excel of even high-level libraries. This runs on an embedded platform where memory is tight. All code is in C. So even for the linear regression we're using now, I have to spell out the equations and make sure nothing overflows. That works quite well, but...
  4. MarcJ

    A Least-squares - fitting an inverse function

    Hello all, I found this thread because I'm trying to do the same thing: measure a distance using a capacitive sensor. As an extra, I'm doing this as the data comes in, so a streaming algorithm would be best. Normal linear regression can easily be used with streaming data, since only summations...
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