-
partially a followup to #838
other statistics for which we should also get outlier robust estimators
cov
...
**acf, pacf**
Dürre, Alexander, Roland Fried, and Tobias Liboschik. 2015. “Robust Esti…
-
This looks like a recent hot topic mainly for machine learning.
Basic idea: use calibration data, separate from estimation/training data, to estimate quantiles and prediction sets or intervals for …
-
By calling a probability distribution function in scipy.stats, the corresponding function in wafo.stats is actually called.
I discovered this when using `scipy.stats.exponweib.fit()` (fitting a Wei…
-
```
s = pd.Series([-1, 0, 0, 0, 1, 1])
print(s.median()) # 0.0
print(dd.from_pandas(s, 2).quantile(0.5).compute()) # 1.0
```
This is also true for arbitrarily large repetitions of this data, e.g.,
…
-
Hello,
Congrats on developing this great package. If I want to model stock returns with `erf`, should I use positive and negative return separatly or I should use all return as intput (X, Y). My ex…
-
based on the first few pages of
http://onlinelibrary.wiley.com/doi/10.1111/j.1467-9868.2012.01044.x/abstract
Zhou, Zhou, and Xiaofeng Shao. 2013. “Inference for Linear Models with Dependent Errors.” J…
-
I've been digging through the source for this class and I can't seem to find where the confidence intervals for the quantile regression coefficients are calculated. Nor can I find what method is used …
-
Thank you for building this excellent library!
I'm using Arviz to plot quantile ESS plots in order to check convergence properties of different samplers in the tails of the target distribution. Whe…
-
Some distributions have no closed form (or `special`) versions and are not tractable. For some use cases we can use approximation that are easier to work with.
example: moment matching for p-values…
-
* Add LMfit Monte Carlo and Emcee to fit?
* labfit has the ability include an output which has error bars on each point in a spectrum based on the uncertainty in the parameters.