*see*: econpy.org), I am more than happy to see Python code like this being created.

- Cholesky decomposition and inverse of positive definite matrices
- Solving an AR(p) time series model using least squares
- Solving Ax = b where A is symmetric positive definite
- White's test for heteroscedasticity
- Breusch-Godfrey test for serial correlation up to order p
- Nonlinear regression, fitting of linearizable nonlinear equations to data
- Performing one iteration of Cochrane-Orcutt procedure
- Iterated Cochrane-Orcutt procedure
- Ljung-Box test for autocorrelation
- Statistics: Computing quantiles
- Gramm Schmidt orthogonalization algorithm in Python
- QR decomposition with Gramm-Schmidt orthogonalization Python
- Gauss elimination in Python
- Computing determinants via diagonalization

Hey, thanks for posting these resources. I'm just getting started with EconPy.

ReplyDeleteThis blog has the potential to be something really valuable for a lot of people. Do you plan on maintaining it?

Thanks for the feedback. I do plan to maintain the blog by using it as a companion to www.econpy.org. If there are any specific types of examples you'd like to see, then please feel free to make a request.

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