estimagic

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### What would you like to enhance and why? Is it related to an issue/problem? Currently, estimagic only supports the standard bootstrap. The Bayesian bootstrap ([Rubin, 1980](https://www.jstor.org/stable/2240875?seq=1)) provides an alternative...

timmens

Two proposals for estimation_table

3

* estimagic version used, if any: `main` branch * Python version, if any: 3.9.10 * Operating System: Windows ### What would you like to enhance and why? Is it related...

ChristianZimpelmann

Add scalar benchmark functions

2

We introduce a benchmark set for estimagic consisting of 283 problems for 78 functions. The functions are based on [a collection of optimization problem functions by Axel Thevenot](https://tinyurl.com/2p8d8c5p). We verified...

luward

Replace fuzzywuzzy

1

## Current Situation We use [`fuzzywuzzy`](https://github.com/seatgeek/fuzzywuzzy) for proposals in error messages (e.g. when an invalid algorithm was requested). Unfortunately, it seems unmaintained. ## Alternatives - [thefuzz](https://github.com/seatgeek/thefuzz) by the same author...

janosg

### Problems 1. Before optimizing the performance of our trust-region subproblem solvers, we need to add a few more tests that assure us that we do not introduce any bugs...

segsell

Add identification diagnostics to estimation functions

1

### Problem In empirical applications we often have weakly identified parameters. This can have two sources: 1. The criterion function for the estimation problem is flat 2. Two or more...

janosg

### Desired Situation - We can calculate the second derivative of vector and scalar valued functions that take parameters as numpy arrays or DataFrames - The three standard hessian formulae...

janosg

Update figures/gifs on optimizer history

2

For the envisioned screencasts, we need black backgrounds and single files instead of the gifs. This got me started, but I am not quite happy with the looks yet. So...

hmgaudecker

### Terminology Assume we have a criterion function `f(params)` and its derivative (gradient or jacobian) `d`. To enforce constraints, the internal optimizer sees a reparametrized version `g(x) = f(r(params))`. By...

janosg

Pandas has a [nice way](https://github.com/pandas-dev/pandas/blob/5f96f2868f6dc2a96c7154003c0e217173d8c050/pandas/compat/_optional.py#L64) of handling imports of optional dependencies. We should check if this can make our code less repetitive.

janosg