docs: documentation of error propagation for iterative algorithms

extended.
This commit is contained in:
Fabian Joswig 2022-02-14 14:06:46 +00:00
parent e80fde6630
commit 3a6fc810b1
2 changed files with 67 additions and 8 deletions

View file

@ -72,9 +72,10 @@ def least_squares(x, y, func, priors=None, silent=False, **kwargs):
fit function, has to be of the form
```python
import autograd.numpy as anp
def func(a, x):
y = a[0] + a[1] * x + a[2] * anp.sinh(x)
return y
return a[0] + a[1] * x + a[2] * anp.sinh(x)
```
For multiple x values func can be of the form
@ -133,9 +134,10 @@ def total_least_squares(x, y, func, silent=False, **kwargs):
func has to be of the form
```python
import autograd.numpy as anp
def func(a, x):
y = a[0] + a[1] * x + a[2] * anp.sinh(x)
return y
return a[0] + a[1] * x + a[2] * anp.sinh(x)
```
For multiple x values func can be of the form