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docs: documentation of error propagation for iterative algorithms
extended.
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2 changed files with 67 additions and 8 deletions
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@ -72,9 +72,10 @@ def least_squares(x, y, func, priors=None, silent=False, **kwargs):
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fit function, has to be of the form
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```python
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import autograd.numpy as anp
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def func(a, x):
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y = a[0] + a[1] * x + a[2] * anp.sinh(x)
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return y
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return a[0] + a[1] * x + a[2] * anp.sinh(x)
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```
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For multiple x values func can be of the form
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@ -133,9 +134,10 @@ def total_least_squares(x, y, func, silent=False, **kwargs):
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func has to be of the form
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```python
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import autograd.numpy as anp
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def func(a, x):
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y = a[0] + a[1] * x + a[2] * anp.sinh(x)
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return y
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return a[0] + a[1] * x + a[2] * anp.sinh(x)
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```
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For multiple x values func can be of the form
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