kappa | What precedes Lambda -

there is a riddle about Typescript I cannot understand:

I'm having trouble understanding an error message I'm getting from my GEKKO model.

For context, this model is supposed to optimize the gas spring force and dimension parameters of a gas-spring assisted door to minimize the operator force required to close the door. My intent is to calculate the required force at a series of angles between 0 and 90 degrees, then sum the absolute value of the force at all angles and minimize that value. There is also a constraint on the gas spring length so the optimization doesn't come up with unrealistic dimension parameters. I've defined the force and other values that need to be computed at each angle as lists of Intermediate variables.

The error appears to be related to one of these lists of Intermediate variables, but I don't know how to interpret "Position: 2" in the error message, let alone "Error in syntax of function string". I've searched in some other answers on here, but I haven't found a clear answer on how to use this position information to troubleshoot the model. What is the message trying to tell me?

I want to have text printed out on the condition that the mouse positions hover over a certain coordinate range for both x and y coordinates. However, the text can not print even if I state in the code that the text should be printed if its on a certain coordinate range. Can anyone offer me some advice towards what I should be doing? Any help can be appreciated.

The code to print the text is after the "// Gamma" comment

I'm trying to test the accuracy of a pre-trained CNN model(densenet121) by using its save weights but got stuck in this error. The code for testing is as follows:

I am trying to integrate a very simple ODE using boost odeint. For some cases, the values are the same (or very similar) to Python's scipy odeint function. But for other initial conditions, the values are vastly different.

The function is: d(uhat) / dt = - alpha^2 * kappa^2 * uhat where alpha is 1.0, and kappa is a constant depending on the case (see values below).

I have tried several different ODE solvers from boost, and none seem to work.

Update: The code below is now working.

In the code below, the first case gives nearly identical results, the 2nd case is kind of trivial (but reassuring), and the 3rd case gives erroneous answers in the C++ version.

Here is the C++ version:

Background

I'm using the irr package in R to generate some inter-rater reliability statistics for a project I'm doing. Here's an example of Fleiss's Kappa using the package's built-in data:

I am using the package circular in R to fit a von Mises distribution to a set of data:

Assuming these definitions of foldTree, a Tree and a function f:

My question seems a little vague so I will provide background context and my reproducible code to try and clarify.

I am interested in classifying crime occurrences in various neighbourhoods of a city, based on each neighbourhood's socioeconomic indicators. My end goal is to be able to generate a reasonably accurate prediction which would suggest the most likely neighbourhood that the next crime should occur. I chose to fit a multinomial regression model, and I am having a hard time interpreting its results.

Here is how my data looks: