# Questions tagged [nonlinear-regression]

Use this tag only for regression models in which the response is a nonlinear function of the parameters. Do not use this tag for nonlinear data transformation.

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### Estimating function - f(x,y) for the given minimums (Python)

I was given 3 minimums of Y = f(X1, X2) such that: Local Minimum1: X1 = 0.20; X2 = 0.30; Ymin1 = 0.70 Local Minimum2: X1 = 0.60; X2 = 0.80; Ymin2 = 0.80 Global Minimum: X1 = 0.85; X2 = 0....
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### Bias of estimated maximum value of a function [closed]

If you fit a nonlinear function f(x) to some noisy (x,y) data, and if f(x) is maximized at x=x', how much positive bias will there tend to be in your estimate of the function maximum f(x')? You expect ...
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### How to deal with Non-Linear prediction intervals with horizontal asymptotes?

I'm using a weibull regression on a data set which reports % total expenditures over time. Time is measured by % of project total completed, therefore neither the dependent or independent variable can ...
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### Using R^2 in nonlinear regression

This page discusses why Minitab does not compute $R^2$ for nonlinear regression. I understand that calculating $R^2$ between the response and the predictor ($y$ vs $x$) is not justified. However, is ...
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### Regression on matrices

Given an equation in the form of $R(\lambda) = \left ( \sum_{i=1}^{4} R_i(\lambda)^\frac{1}{n} \right )^n$ where $R$ is a $m$ by one matrix and a number of data matrices for $R$, can nonlinear least ...
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### Regularization (L1 or L2) for non-linear parameters

I was wondering whether it is possible to regularize (L1 or L2) non-linear parameters in a general regression model. Say, I have the following cost function, where 𝑝 is a 3𝑑 vector of fitting ...
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### Non-Linear regression and variance misspecification

Given a non-linear regression model for cross-section data $$y_i = f(x_i,\theta_0) + \epsilon_i,$$ where it is assumed that $\mathbb E[y_i\lvert x_i] = f(x_i,\theta_0)$, I understand that it is a ...
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### Confidence intervals of percentiles in non-linear regression

I'm fitting a log-logistic model, $Y=1/\left(1+10^{((\log a-\log X)/b)}\right),$ to toxicity data ($X$ are concentrations and $Y$ are mortalities) using SPSS and Graphpad Prism. I get the fitting ...
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### Multivariate Nonlinear Mixed Effects Model

I want to estimate a multivariate nonlinear mixed effect models where the random effects are not assumed to be normal. What approach should I take ?
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### Fitting curves in Jupyter Notebook without using the fit function [closed]

For a task for school, I have to write my own fit function by using the least squares method. The problem is I don't know how to do that, specifically I don't know how to minimize my function to ...
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### Forecasting/predicting total sum of donations (following GLM with poisson family and log link)

I am trying to predict the total sum of donations that Monica will receive on https://www.gofundme.com/f/stop-stack-overflow-from-defaming-its-users/ I copied the data and summed for all days the ...
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### Importance of absolute values of the covariance matrix in the nonlinear mixed models

I am fitting a nonlinear mixed model (three-parameter logistic function) without any hierarchical structure. I have adopted an unstructured variance-covariance structure for the random effects. Is it ...
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### Polynomial regression : how to find the best polynomial degree ? Chi2 or equivalent already built-in in Python numpy?

I am studying the stability of numerical derivatives as a function of the step I take to compute these derivatives. With a derivative with 15 points (obtained by the finite difference method), I get ...
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### What is the name of this simple model? [duplicate]

Given data $d_i$ captured at corresponding times $t_i$, my model is $$d_i = \sum_{j=1}^m b_j f_j(t_i,θ) + e_i$$ where as usual $e_i \sim N(0,σ^2)$. In other words, the data is expanded in $m$ ...
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### Survival Analysis/Customer Attrition Model for Balances

I’m looking to model balance, meaning dollars, decay(attrition). In brief, I have time series customer data, which is aggregated to get customer’s balances for a specific product. Over time, the ...
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### Extension of Lee-Carter model with parametric functions of age and time

A standard model of mortality is the Lee-Carter model where Deaths at age $x$ and time $t$ are given by $D_{xt}\sim Poisson(E_{xt}\mu{xt})$. $E_{xt}$ and $\mu_{xt}$ are, respectively, the average ...
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### How to interpret “quantile residuals”

The DHARMa package in R aims to provide scaled (quantile) residuals that, according to the DHARMa vignette, "can be interpreted as intuitively as residuals from ...
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### Literature review on non-linear regression

Does anyone know of a good review article for the statistical literature on non-linear regression? I am primarily interested in consistency results and asymptotics. Of particular interest is the ...
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### Interpretation of a quadratic term on a log transformed target variable

I've done some searching and found several posts related to this, e.g.: In linear regression, when is it appropriate to use the log of an independent variable instead of the actual values? Suppose I ...
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### Grouped Logit vs. Non-Linear Least Squares vs. Negative Binomial w/ Exposure?

I'm currently working on a project looking at the effect of competition on the type of appeals candidates make in their campaign advertisements. My dataset consists of a list of candidates, the ...
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### Checking non linear effects in LASSO regression

This might be a weird question and I understand that LASSO is mainly using as a variable selection method. But I want to know that is it possible to check non-linear effects of a LASSO logistic ...
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### Bell-curve shape regression [duplicate]

I am trying to fit some data that looks like a bell-curve: we reach a maximum at some value close to the mean, then the graph falls towards zero as we get further away from it. I am not the "owner" of ...