bic | A C interpreter and API explorer | Interpreter library

I'm writing an app in WPF, trying to use the MVVM-design pattern (which is new to me). I have a DataGrid bound to an ObservableCollection.

Delete the currently selected DataGrid-row using a 'Delete'-button. I've tried a plethora of forum-posts and videos to find a solution. The solution has probably stared me right in the face several times, but at this point I'm more confused than I was when I first started.

Any assistance would be appreciated.

ViewModel (updated with working code, thanks to EldHasp):

looking to have the r squared, aic, bic, and deviance values presented for each of the four models here in the merged output

I'm trying to fit a generalized linear mixed model with glmmTMB

I want to replace _ with \_ in a string.

I am quite new to programming in general. I am working in Python and I am encountering some difficulties.

I have two functions with 4 varaiables each, they both contain the same variables. For the variables I created 4 lists with the different values for the variables. Now I would like Python to calculate/generate all the possible outcomes for the two functions.

Subsequently, I would like to plot these outcomes in a scatterplot but for now is there someone that can help me with this problem.

I have to tried to make a list with all combinations but I cannot link this to the 2 functions. So x1 can be 6, 7, 8. x2 can be 4, 5, 6. x3 can be 2, 3, 5, etc

Thanks a lot in advance!

In this question / answer from 5 years ago about logLik.lm() and glm(), it was pointed out that code comments in the R stats module suggest that lm() and glm() are both internally calculating some kind of scale or dispersion parameter--presumably one which describes the estimated dispersion of the observation values being predicted by the regression.

This naturally begets another question: if it's truly a real parameter being estimated by the fit algorithm somewhere (or even if it's just some kind of implicit / effective parameter), how do I access this parameter from the resulting fit object?

I've produced a MWE (plus supporting setup / plot code) below:

• Part 1 constructs some simulated input data, which we'll fit to a straight line (implying two fit parameters are expected). Given the question is about a hidden, internally modeled dispersion parameter, I wanted to make sure the fit algorithm is forced to do something interesting, so therefore 10% of the points have been deliberately modeled as outliers. If you understand what's shown in the plot below, then you can probably skip reading this portion of the code.

• Part 2 is the main body of the MWE, illustrating the point that my question is asking about: it runs glm() on the input data and examines some of the results, demonstrating that logLik() claims three parameter estimates, in apparent disagreement with glm() which seems to give two.

• Part 3 just produces a little supplementary figure based on the input data and results. It's only included for completeness & reproducibility; you can probably skip reading it too.

I have list1 let's say:

Please, how do I assign the N, Log-likelihood, AIC, and BIC values to each of the multivariate regression models in a merged gtsummary table output?

I am a Rmerteur trying to fit additive multivariate models adding higher-level variables to subsequent models (see below example). Meanwhile, I could not retain the N, Log-likelihood, AIC, and BIC values for each model fit once I merge the separate models. I need the estimates to compare the fit across the models.

Is there an easy way to get this done?

Thank you for your help!

I am attempting to reproduce the filters used in an ARIMA model using stastmodels recursive_filter and convolution_filter. (My end objective is to use these filters for prewhitening an exogenous series.)

I begin by working with just an AR model and recursive filter. Here is the simplified experimental setup: