Questions tagged [non-linear-regression]

In statistics, nonlinear regression is a form of regression analysis in which observations are modeled by a function which is a nonlinear combination of the model parameters and depends on one or more independent variables.

732 questions
18
votes
2 answers

Multinomial logit in R: mlogit versus nnet

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 of discrepency between the coefficients and standard…
splinter
  • 3,727
  • 8
  • 37
  • 82
13
votes
2 answers

Calculation of R^2 value for a non-linear regression

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 performing most of our work in SigmaPlot over to R and for…
sinclairjesse
  • 1,585
  • 4
  • 17
  • 29
9
votes
1 answer

Is deep learning bad at fitting simple non linear functions outside training scope (extrapolating)?

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 can think that neural network might not be able to…
9
votes
1 answer

Keras model to fit polynomial

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. Since this is my first time working with neural…
FloodLuszt
  • 137
  • 2
  • 6
8
votes
2 answers

non linear regression with random effect and lsoda

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 equation with fixed coefficients (a damped…
denis
  • 5,580
  • 1
  • 13
  • 40
8
votes
1 answer

Non-linear regression in Seaborn Python

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 below that is the dataframe I am using, df. Note I have…
AngusTheMan
  • 564
  • 1
  • 6
  • 15
8
votes
2 answers

How can you remove only the interaction terms in a polynomial regression using scikit-learn?

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_only = True, keeps only the interaction terms such as…
8
votes
3 answers

Finding non-linear correlations in R

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 and quick way to do this? I have tried building a…
dorien
  • 5,265
  • 10
  • 57
  • 116
8
votes
3 answers

Distinction between linear and non linear regression?

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 linear (polynomial) regression model However, in…
7
votes
1 answer

Find initial conditions for nonlinear models using the nlsLM function

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 <- 0.946 b <- 2000 k <- 50000 nr <- 25 na <- 4000 nd <-…
Pierre
  • 435
  • 4
  • 14
7
votes
1 answer

How to perform piece wise/spline regression for longitudinal temperature series in R (New Update)?

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 implementation in R in SO, got an initial idea how…
Andy.Jian
  • 417
  • 3
  • 15
7
votes
1 answer

Testing the Proportional Odds Assumption in R

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 understanding is that I need to test that it is…
7
votes
2 answers

Nonlinear multiple regression in R

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 1 -60 -45 615 720 …
japem
  • 1,037
  • 5
  • 16
  • 30
6
votes
1 answer

Using GPy Multiple-output coregionalized prediction

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, my results keep getting worse. I have tried…
6
votes
2 answers

Getting covariance matrix of fitted parameters from scipy optimize.least_squares method

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 fitted parameters in order to get error bars on the…
1
2 3
48 49