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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Nonlinear sin model with brms

I try to fit sin function with brms using next code: ...
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8 views

non linear mixed effect model with unbalanced data

I am using nlme to model the growth curves of individuals that are in 4 different groups, using R. The number of individuals in each group is completely unbalanced (n1=344, n2=51, n3=34, n4=25). ...
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Code incorrectly determines that a poor fit is a good fit

I'm trying to find the best polynomial fit for a set of data. It calculates the AIC for each polynomial fit of a certain degree, and then chooses the one with the lowest AIC. To my knowledge (which I ...
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Error on nonlinear regression by bootstrapping [duplicate]

There are several methods with which I am familiar for calculating the error / margins on a nonlinear regression fit. The standard method I think is the delta method used in Prism (described here): ...
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Error while curve fitting in R [closed]

I need to fit the curve y = K + B*exp{ a*(log x) + b*(log x)^2 + c*(log x)^3 }. Where a, b, c, K, B are unknown parameters. I just have 5 data points which are, <...
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Multiple Non-linear Regression with Function-based regression and Machine Learning models

I'm working on an application of Multi-nonlinear regression. Initially, I tried this algorithmically by creating a polynomial of the form A(x^p * y^q * z^r). I saw ...
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27 views

Multivariate, nonlinear regression in R

I am trying to make a chemical concentration curve, but it has been so long since I have had to use any type of math I'm having trouble getting going through iterations to find the best fit. The ...
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1answer
28 views

A non-linear regression model for within subject observations

I am trying to perform the equivalent of a repeated-measures ANOVA using data that have a non-linear relationship. There are two independent variables: Spacing between stimulus (10, 20, 35, 45, 60), ...
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1answer
23 views

Modeling two variable non-linear regression

I would like to fit a model to the data set that has two predictors, wind and relative humidity, and the response is inoculum production. The response to increasing in RH is sigmoid. I am not really ...
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Nonlinear Regression with Correlated Error

Assume I have two data sets: Experimentally measured data y for known values $x$. Assume the nature of the error in $y$ is random only and $\sigma_y$ is known/estimated. Simulated (deterministic) ...
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Question regarding statistical methodology that involves logistic regression

I used following simulated data using R to demonstrate my problem. require(lmtest) require(splines) x=rnorm(20 ,0,1) y=rep(c(0,1),times=10) Although my simulated ...
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How can I concentrate out parameters entering linearly in a partially non-linear regression?

I have model $$y_i = x_i^\top\beta + \delta \exp(w_i\eta) + \epsilon_i$$ in setting up a non-linear regression problem $$\min_{\beta,\delta,\eta} \frac{1}{2N} \sum_i^N (y_i - x_i^\top\beta - \delta \...
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When to use non-parametric regression such as kernel, generalized additive model, spline, and polynomial?

I understand that kernel regression is a form of non-linear/non-parametric regression. However, I know you can also use generalized additive models for non-linear regression, as well as polynomials ...
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52 views

Standardized MSE-style metric for nonlinear regression, chiefly neural networks

I am interested in neural network regression and if I have a model that has a level of performance that I deem acceptable. I am comfortable using MSE as a loss function, but I am not keen to use MSE ...
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32 views

Regression model form

I have the following exercise: US.pop dataset from car package contains information about USA population from 1790 to 1990. Find regression model in form of $y = a / (1 + \exp((b-x)/c) )$ for ...
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Why does the R2 value of regression improve on retraining neural network

I have two sets of data samples. Set 1 has 1900 samples and Set 2 has 1000 samples (none of which overlap with Set 1). I am using Set 1 to train my neural network and then testing it in Set 2. On ...
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Trouble fitting my data with non-linear Regression model

I have a dataset that contains tree height and diameter measurements among the tree stem. I tried to fit my data with GNLS in R, but I'm getting this "step halving factor reduced below minimum in NLS ...
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Non linear regression: $y = f(x_1) + g(x_2 - h(x_1))$

Suppose my dependent variable $y$ is generated from continuous variables $x_1$ and $x_2$ by the model, $$y = C + f(x_1) + g(x_2 - h(x_1)) + \text{noise},$$ where $f$, $g$, $h$ are smooth nice ...
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1answer
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Examples of “one to many” for RNN/LSTM

Are there any examples dealing with "one to many" kind of LSTM? Basically I am trying to build a model which takes an input vector $a$ and gives an output of $[b_1; b_2 ;b_3; b_4, \ldots; b_n]$ where ...
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1answer
27 views

How to model counts of a categorical variable?

I'm interested in assessing the impact of various covariates (age, sex, Charlson comorbidity score, etc.) on the incidence rate of a pulmonary event. However, the event is not binary. Each patient ...
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Hypothesis testing for nlsList fitted coefficients

I am trying to test in R if the coefficient R10 (soil respiration at 10 °C) is significantly different between two plant types (Type1 and Type2). For this, I fitted a modified Lloyd-Taylor function ...
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How to fit a set of curves having some free and some shared parameters?

The problem I have a data set with 1 dependent and $N$ independent variables $x_1,\dots ,x_N$ (all real numbers), and need to fit a (nonlinear) function/curve $$ f_i(x_i; p_1,\dots ,p_{k_F}, r_1, \...
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como eu posso ajustar parameteros um sistema com duas equações com a função nls()? [closed]

I Ned to fit this system of equations: I'm using nls.lm(), but want to use the nls() function # rm(list= ls()) df=read.table( text =" 0 0.010000000000000 0 0....
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1answer
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Hard in calculating predictor‘s Relative Importance for GAM?

Although there is no agreement upon "relative importance for predictors" with (even) linear models (one possible definition: lmg method), I would still want to know whether there are some acceptable ...
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Regression problem — which methods are appropriate?

Given: A non-differentiable, non-smooth function $f(p,q) \rightarrow R$ A set of points $S=\{(x_0,y_0), \ldots, (x_n,y_n)\}$ Bounds as $p_{min} < p < p_{max}$, and $q_{min} < q < q_{max}$...
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58 views

Multi State Models to analyze/plot disease progression and probability of being misdiagnosed

Let's say that I have the following dataset containing information for 100 patients that have been followed up for a certain number of years to check if they develop a certain disease. We know up-...
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Correct Specification for Censored Data

I have some construction data, which shows the starting year of unfinished and finished projects but don’t have any information on the completion time of finished projects. If I had data on the ...
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1answer
58 views

Residual Analysis assumptions for non-linear regression

I understand Regression analysis relies on the following assumptions about the residuals: Normally Distributed (normal plot of residuals) Be independent of each other (random and data must be time ...
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62 views

Is there a measure of “complexity” for linear/nonlinear model terms?

My apologies if this is grossly misunderstood or mis-worded, but I've been mildly bugged by a question to which I've not found a satisfactory answer. I can't say that I have seen a discussion about ...
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1answer
30 views

Model to capture non-linear patterns in data using R

I've fitted a linear model using: m2 <- lm(GPP ~ rainfall + summer.temp + parcel.size + soil.nutrients, data=gpp) As seen from the partial relationship plots ...
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Justification for LST model

Let’s say I have a linear model specification but I believe that a logistic smooth transition model would be better. Is there any evidence I can take from the linear model that would point me in ...
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Initial conditions for nonlinear models using the nlsLM function

I have a data frame containing 70000 rows. For each row, I am trying to apply the nlsLM function (minpack.lm package) to find ...
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1answer
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Estimating a Conditional MNL in mlogit

The Problem I am trying to estimate a conditional multinomial logit model where each household has an observed house choice outcome given a set of alternatives. Each set of alternatives is unique to ...
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54 views

Goodness of fit test for any regression model?

Is there a general goodness-of-fit test for any kind of regression model? My problem is that I have a deep neural network that tries to predict some real value labels using high-dimensional input. The ...
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deciding on the form of the formula in multivariate nonlinear regression

dear members, lets say I have one response variable and two predictors (non linear): Y1, the response variable, and two predictors, X1 and X2. Using nonlinear least squares estimation, ...
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How to perform joint estimation of parameters from two NLS-regressions in R?

First of all, I am new to the board so excuse me if I am not writing this post in the most optimal way. That aside, I am trying to run some models on optimal entry timing for successive product/...
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2answers
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The non-linear extra sum of squares? What is this?

I encounterd in the article I read the term the non-linear extra sum of sqare with the reference to Bates and Watts 1988. I do ...
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56 views

Fully connected layer vs Multiple parallel dense layers for multivariate nonlinear regression?

I'm trying to tackle a multivariate nonlinear regression problem that takes around 20 inputs and outputs around 200. I have a set of known points and need to come up with a performant neural network ...
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What does bandwidth in kernel regression mean?

here https://stat.ethz.ch/R-manual/R-devel/library/stats/html/ksmooth.html is bandwidth explained as "the bandwidth. The kernels are scaled so that their quartiles (viewed as probability densities) ...
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1answer
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Extracting the linear equation for a circular-circular regression

I am trying to create a predictive model using a relationship found by the lm.circular function from the circular package. The ...
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43 views

How to do a sensitivity analysis on a non-linear equation?

In the company, it is very difficult to actually do quotations for our customers properly because we do not have perfect information regarding the factors that affect the cost and profit. So I created ...
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Minimizing numerically a nondifferentiable function

Many (likelihood) functions are not differentiable at the optimal point. Does this cause problems a) in the numerical methods used to minimize the function based on the gradient? b) in the statistical ...
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Estimating the trend over time

I have series of data which is quarterly. I want to analyze is there any significance increase over time. With my little knowledge about ARIMA and time series I used auto.arima function ...
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1answer
34 views

Linear regression using running parameters

I always asked myself what was the right method name for a simple linear regression using running parameters. I mean that instead of using constant mean $\bar{y}$ or $\bar{x}$ for the estimation of $ ...
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About Multicolinearity in Support Vector machine based regression model

Is there any need to check multicollinearity for Support Vector machine based Regression model(for prediction)? If yes, then how it can be handle?
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1answer
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Prediction in logistic regression with prediction criteria ranges

I’m not sure how to best explain my problem but I’ll try. I can’t be too specific because this is a homework assignment; I just would like some guidance from the experts on how to approach it. So I’...
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How to run a nonlinear repeated measure multilevel regression?

I'm working with a colleague on a project that requires analysis a fair bit beyond my expertise. Background We are looking at recall of events in films. We broke down the film by Events and by shots ...
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1answer
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Regression model using combination of ranges/parts

My main goal is making predictions using a nonlinear model that have many independent variables. I would like to split my numerical independent variables into ranges/parts. Then to use a combination ...
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1answer
28 views

I need help with choosing a mid-long term forecastic method for this demand

I am trying to forecast the demand of a product for the next 36 months, based on its sales history. The demand plot is shown below. I honestly don't know what to do with it. I tried linear and non-...
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How can I determine, in what extent the fit to experimental data is good in Matlab?

I have experimental spectrum in which y-axis is intensity values, and x-axis is frequency values. Int - array of experimental intensities (y-axis). w - array of frequencies (x-axis). I know the view ...