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I am using the maximum likelihood method to estimate a set of parameters. Now I am going to use mle function from the stats4 package in R to make a profile likelihood for one of the parameters. To do that, I need to fix one of the parameters when I call the mle function. Here is the code:

I'm trying to minimize a function w.r.t. a list x0 of shape (30), but I got the error:

In my C# program I have a dataset where each data point consists of:

• a stimulus intensity (intensity) as x-coordinate
• the percentage of correct response (percentageCorrect) to stimulus as y-coordinate

When the intensity is low percentageCorrect is low. When the intensity is high the percentageCorrect is high. The function graph is an S-shaped curve as the percentageCorrect reaches an asymptote at low and high ends.

I am trying to find the threshold intensity where percentageCorrect is half way between the asymtotes at either end (center of the S-shaped curve)

I understand this to be a function maximization problem that can be solved by the Nelder Meade Simplex algorithm.

I am trying to solve my problem using the Nelder Meade Simplex algorithm in mathdotnet and its IObjectiveFunction parameter.

However, I am having trouble understanding the API of the NedlerMeadeSimplex class FindMinimum method and the IObjectiveFunction EvaluateAt method.

I am new to numerical analysis that is pre-requisite for this question.

Specific questions are:

• For the NedlerMeadeSimplex class FindMinimum method what are the initialGuess and initialPertubation parameters?
• For the IObjectiveFunction EvaluateAt method, what is the point parameter? I vaguely understand that the point parameter is a datum in the dataset being minimized
• How can I map my data set to this API and solve my problem?

Thanks for any guidance on this.

Please ignore the messiness, still a noob at this. Basically, I have a function:

I am trying to use scipy.optimize.minimize to fit parameters for a multivariate function, however, regardless of how many noise free data points I am providing to the optimizer, the optimizer could not converge to a correct (or close) answer.

I wonder if there is a mistake in the way I am using the optimizer but I have been scratching my head to find the mistake. I would appreciate any advice or guesses, thanks!

Below is an example structure of a document:

I have never used Python before, coming from a Javascript background.

I need to loop through the array in the csv and compare it with the date in the today variable. Then return where each item is expired or valid. Also how many days are left to expiry or how many days ago they expired.

Any pointers?

I'm trying out the tidy methods that Hadley Wickham describes in this video: https://www.youtube.com/watch?v=rz3_FDVt9eg&t=1902s. It's straightforward to get certain statistics this way, as long as there is only 1 row in the tidied data frame, but the slope of each linear model is buried in the 2nd row of a tidied data frame made with Broom. My code is very similar to Hadley's, and looks like this.

I am trying to display one course and to update course topic, using graphql and apollo-server. This is my code: