Questions tagged [nls]
`nls` is an R routine to fit nonlinear regression models of the form $y = f(x B) + e$
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questions
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fitting specific formula/model in r - model possibly not identifiable
I would like to fit the following formula in R:
y ~ alpha *(x1_0 * x2_0 * beta_0 + x1_1 * x2_1 * beta_1)
Here: alpha, ...
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0answers
7 views
fitting multiplicative non linear model in R
I have samples per month over several years (assuming stationary behavior). My data contains an independent variable: hours (representing available hours per month). The model to be fitted should ...
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0answers
11 views
Nonlinear regression with variables that are directly dependent on each other
I am performing a nonlinear regression analysis (with the nls function in r) to estimate the constant parameters for a proposed equation. My equation has 4 variables L, G, m, and S. G and S are not ...
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2answers
103 views
Interpreting and troubleshooting nls in R with quadratic plateau model
I am trying to run a quadratic plateau model on some proportion data where values are bound between 0 and 100. I would like some help troubleshooting some errors I have encountered, and correctly ...
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3answers
39 views
How do you compare linear model vs non-linear (nls) model in R?
I am trying to model some data, and as part of the modeling, I tried linear model (using lm function) and non-linear model (using nls) function.
Model 1 : a linear model which has degrees of freedom ...
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0answers
84 views
Starting values for an nls model in R [duplicate]
I'm trying to fit an exponential model using nls, but I don't know how to select the starting values for the parameters. I know this question has been answered multiple times, but I spent some days ...
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15 views
multiple fixed effects in non-linear model
I'm trying to understand how to include an interaction/multiple fixed effects into a non-linear model.
I have a data set with two independent variables (temperature and nutrient concentration) and ...
0
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1answer
32 views
Sine curve fit and model tunning using nls in R
I acquired data (motor adaptation =y in function of delays =t ) which I expect to look like a sine wave. I am trying (1) to fit a sine curve in my data and (2)to estimate the best model/parameters. I ...
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0answers
68 views
Sine curve fit using nls in R
I acquired data (motor adaptation $y$ as a function of delays $t$ ) which I expect to look like a sine wave. I am trying (1) to fit a sine curve in my data and (2) to estimate the best model/...
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0answers
17 views
Sine curve fit using lm, nls and nls2 in R [closed]
I acquired data (motor adaptation =y in function of delays =t ) which I expect to look like a sine wave. I am trying (1) to fit a sine curve in my data and (2)to estimate the best model/parameters.
I ...
0
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1answer
48 views
Comparing time series data between three treatment groups (in R)
I have time series data where the response is decreasing over time. The rate of the decrease is supposed to depend on the treatment (the concentration of a drug). By looking at the data I am not sure ...
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0answers
26 views
Shared parameters similar to stats::nls() using “[]” but for minpack.lm::nlsLM() or similar?
I am looking for a method similar to the very convenient "[]" notation in stats::nls(), for estimating certain parameters separately (while sharing others) for subgroups within my data, which works ...
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0answers
42 views
r - Understand goodness of a fitted curve [duplicate]
I had to find the equation of curve that represent my data. After trying different function, I got a models that seems fitting my data, at least by plotting them. But this is it. I have no idea how to ...
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1answer
359 views
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1answer
112 views
Constraining parameters in NLS in R to be less than a value, or greater than a different value
The nls function in R comes with upper and lower arguments to specify the upper or lower ...
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0answers
25 views
Nonlinear fit in R only works with tightly restricting parameter bounds [duplicate]
I have a reproducible example here with an attempt to use nls to fit a nonlinear function:
y = ax/(b+x) + c
Even when I set the starting values to be a good, ...
0
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1answer
621 views
Singular gradient erros, NLS in R
I'm trying to fit nls(Mound~ a*kg.bag.collar^b + c, start = list(a = 83, b = -.5, c=100), data=test) using the dataset here. I've fit it without trouble without the ...
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0answers
403 views
NLS model comparisons by ANOVA
I am comparing NLS models from two groups, males and females. I compared the models by ANOVAs, but I am hesitating which is the correct model comparison to use:
a) Subgroup Males vs Subgroup Females
...
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0answers
79 views
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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0answers
18 views
Estimate the Beta Coefficients, and then find an algorithm
Referring to the photo, I need to report my beta coefficients as functions of observed Xi and Yi. I tried to reduce by taking the log of both sides but It seems I can't reduce this model because it is ...
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0answers
379 views
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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0answers
104 views
comparison of more than one multivariate nls models in r
dear members,
I am trying to identify which of the two multivariate nls models is more of a good fit. I came to know that you can use anova and f tests for univariate nls models to know ...
1
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1answer
1k views
How to know if a parameter is statistically significant in a “curve_fit” estimation? [closed]
I use curve_fit from scipy to estimate parameter values from a specific function.
...
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0answers
76 views
Reproducing non-linear sigmaplot regression with nls()
I'm trying to reproduce a non-linear regression with various similar datasets.
The original regressions were performed by sigmaplot with a modified morrison equation and estimates for parameters E=2,K=...
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0answers
2k views
How to fit exponential y=A(1-exp(B*X)) function to a given data set? Especially how to determine the initial start parameters? [duplicate]
I have a data set in which $y$ is roughly related to $\log(x)$. Now I wish to fit the curve $$y=A(1-\exp(BX))$$
When I use R and the nls2 function, then I ...
2
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0answers
242 views
Why do different parameterizations give different results for nls?
Goal
I'm trying to fit a four-parameter logistic (A+(B-A)/(1+exp((xmid-input)/scal))) in R, using nls and SSfpl, to fit two datasets that share the upper, lower, ...
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1answer
1k views
Standard errors for non-linear least squares in R
I have a question on standard errors for non-linear least squares in R. With the built-in function NLS and a hand-made function I get different SE and I don't understand why. I will try to expose ...
2
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0answers
466 views
Fitting a sinusoidal curve only with max-min values
I have a series of high-low tide values, approx. every 6h, and each one has the corresponding time. I would like to get (an estimation of) the values between each record. I was thinking I could create ...
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1answer
2k views
Simultaneously curve fitting for 2 models with shared parameters in R
Hi I am trying to curve fit 2 models (Van Genuchten & Mualem) with shared parameters in r. The models are:
...
1
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1answer
220 views
Difference between probit of log(x) and probit using inverse lognormal cdf of x
Topic: probit and logprobit regression.
Context: I have to implement a model of size at maturity in a wild population and I must choose a binomial linear model to estimate the parameters based on ...
2
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0answers
227 views
Bootstrapping of nonlinear regression residuals: why does the model fitting fail?
I am trying to define a range of uncertainty associated with each estimate of the parameters of a nonlinear model:
...
0
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1answer
322 views
Fitting a non linear equation to a dataset
I am working on fitting an equation from a dataset. In my dataset I have two variables where I am interested at and I looking a function that gives me the value the free variables that I use in the ...
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2answers
607 views
How to calculate p-value for a parameter given confidence interval when null hypothesis != 0
Given the dataset:
...
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1answer
1k views
2
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1answer
2k views
nls() gradient error in fitting growth curve data
I am trying to model the following data on promotional budget and customer awareness. The idea is, at some point, increase in budget doesn't have any further impact on awareness; it saturates.
...
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2answers
1k views
nls() function in R not fitting well when calculating Kd
I'm trying to calculate Kd with the following R code but my model is clearly wrong (see image). How has nls() converged so poorly? How can I use it to find a better ...
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1answer
300 views
Calibration of a computer code: how to deal with parameter vectors such that for some data points the code doesn't converge
I have an experimental data set $D=\{\mathbf{x}_i,y_i\}_{i=1}^N$, and a computer code with inputs $\mathbf{x}$ and calibration parameters $\boldsymbol{\theta}$, returning a value $s=f(\mathbf{x},\...
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1answer
426 views
How can I combine NLS models in a way as is done with linear regression models in Path Analysis
I have a structural equation model that includes several paths that are actually non-linear (built in with the lavaan package for R). I have used polynomials in order to model these non-linear paths. ...
0
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0answers
491 views
Curve fitting - linear vs non-linear
Dose Survival
1.044316 0.7085001
2.017041 0.2764831
3.042148 0.1498388
4.058954 0.0451514
5.098904 0.0145274
I have two models to fit the data: ...
0
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1answer
887 views
Fitting LPPL model using R
apologies if this appears too simplistic/poorly worded a question, this is my first time coding in R
I am attempting to fit the LPPL model to a price series in order to test for its predictive power ...
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1answer
3k views
nonlinear least squares versus maximum likelihood in R, nls() or nlm()?
I am estimating the model $$E(Y|X) = Pr(Y=1|X) = \alpha_0 + (1 - \alpha_0 - \alpha_1)\phi(X'\beta),$$ where $\alpha_0$ and $\alpha_1$ are parameters, $\beta$ is a $p$-length vector of parameters, $X$ ...
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1answer
1k views
Comparing two models using anova
I have following two models (fit1, fit2) estimated using nls approach. I want to compare their goodness using anova, and the results follows:
...
3
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1answer
704 views
I used the function SSfpl (in R) for finding out the correct initial parameters. Why aren't they right?
This is my data:
I used SSfpl for finding out the correct initial parameters
nls(y~ SSfpl (-x, b1,b2,b3,b4), data=estatus)
And with these initial parameters, I used
nls(y~b1 + ((b2-b1)/(1 + exp(...
0
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0answers
125 views
What do the parameters A, B, and C do in an equation of the form $Y = A + Be^{CX}$? [duplicate]
I have read this article and those linked to it, but I am still having difficulties fitting a function of this form to data I have using the nls function in R. Invariably, I fail to get convergence ...
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0answers
1k views
how does nls model work?
I am trying to understand how nls model works.
Let's say I have data frame mtcars and like to do this:
model<-nls(mpg~disp)
but getting this error:
...
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2answers
5k views
2
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1answer
755 views
4th parameter of Boltzmann sigmoid must be greater than .9 in R
I'm trying to fit a 4 parameter boltzmann sigmoid and get an error: "Error in nls(y ~ a0 + (a1 - a0)/(1 + exp((a2 - x)/a3)), start = list(a0 = max(y), :
singular gradient"
I have figured out that ...
0
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1answer
153 views
Debugging in R when using nls
How to correct a nls estimator when I get an error message that: step factor 0.000488281 reduced below 'minFactor' of 0.000976562
The full problem:
...
0
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1answer
549 views
Why do the predictions of a linear (log-log) model not approximate those of a nonlinear (power) model?
I am having trouble using a linear (log-log) model to approximate the predictions of a nonlinear (power) model.
I wish to plot the predictions of the linear model on untransformed axes, and I believe ...
1
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1answer
372 views
Testing difference between two non linear growth curves
I would like to identify the significance of the difference between two growth curves with the same formula but different parameters. The dummy data generated by the code produces a normal spread of ...
