Screenshot demonstrating the use of Excel's Solver: I have a task to automate a certain excel worksheet. The worksheet happens to implement a logic with an excel plugin called Solver. It uses a si...

I am using scipy.optimize's least_squares method in order to perform a constrained non-linear least squares optimization. I was wondering how I would go about getting the covariance matrix of the f...

I am running a polynomial regression using scikit-learn. I have a large number of variables (23 to be precise) which I am trying to regress using polynomial regression with degree 2. interaction_...

I have built several generalised nonlinear least squares models (exponential decay) with the R package nlme and the contained gnls() function. The reason I do not simply build nonlinear least squar...

I am facing a problem I do not manage to solve. I would like to use nlme or nlmODE to perform a non linear regression with random effect using as a model the solution of a second order differential...

I have been facing a problem recently where I believe that a multiple-output GP might be a good candidate. I am at the moment applying a single-output GP to my data and as dimensionality increases,...

In Machine Learning, we say that: w1x1 + w2x2 +...+ wnxn is a linear regression model where w1,w2....wn are the weights and x1,x2...x2 are the features whereas: w1x12 + w2x22 +...+ wnxn2 is a non...

I have about 90 variables stored in data[2-90]. I suspect about 4 of them will have a parabola-like correlation with data[1]. I want to identify which ones have the correlation. Is there an easy an...

Assuming we have the below function to optimize for 4 parameters, we have to write the function as below, but if we want the same function with more number of parameters, we have to rewrite the fun...

Here is a data set: df <- data.frame('y' = c(81,67,54,49,41,25), 'x' =c(-50,-30,-10,10,30,50)) So far, I know how to fit a sigmoidal curve and display it on screen: plot(df$y ~ df$x) fit &lt...

I am trying to create a simple deep-learning based model to predict y=x**2 But looks like deep learning is not able to learn the general function outside the scope of its training set. Intuitively...

I am using the nlsLM function from the minpack.lm package to find the values of parameters a, e, and c that give the best fit to the data out. Here is my code: n <- seq(0, 70000, by = 1) TR &lt...

Here I have temperature time series panel data and I intend to run piecewise regression or cubic spline regression for it. So first I quickly looked into piecewise regression concepts and its basic...

As per the description given below: 'if an input sample is two dimensional and of the form [a, b], the degree-2 polynomial features are [1, a, b, a^2, ab, b^2].' sklearn.preprocessing.PolynomialFe...

I am trying to do a simple forecast of future profit of an organization based on the past records by using regression. I am following this link. For testing purpose, I have changed the sample data ...

I have the following dataframe that I wish to perform some regression on. I am using Seaborn but can't quite seem to find a non-linear function that fits. Below is my code and it's output, and belo...

I generated some data from a 4th degree polynomial and wanted to create a regression model in Keras to fit this polynomial. The problem is that predictions after fitting seem to be basically linear...

I want to run a multinomial logit in R and have used two libraries, nnet and mlogit, which produce different results and report different types of statistics. My questions are: What is the source...

I have been working on a curve fitting script which fits 3 exponentially modified Gaussians (EMGs) to a convolved curve. My base function is similar to a Gaussian distribution, but includes a third...

I have a model equation let's call it eq_m: that I know my dataset follows, I am trying to fit my data to eq_m so that I can use the fitted parameters to predict new data. However this eq_m is...

I am working in R with a response variable that is the letter grade the student received in a specific course. The response is ordinal, and, in my opinion, seems logically proportional. My understa...

My nonlinear mixed-effects model regresses body mass (bm) on age. I would like consider that brood is nested within year, but as a brood can only occur in one of the seven years that are in the dat...

I'm trying to run a nonlinear multiple regression in R with a dataset, it has thousands of rows so I'll just put the first few here: Header.1 Header.2 Header.3 Header.4 Header.5 Header.6 Header.7 ...

I would first like to say, that I understand that calculating an R^2 value for a non-linear regression isn't exactly correct or a valid thing to do. However, I'm in a transition period of perform...