Use this tag only for regression models (q.v.) in which the response is a nonlinear functions of the *parameters* (not because it's a nonlinear function of the *predictors*).

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17 views

Regression analysis of a correlation coefficient

I have a time series of the 250 day historical correlation and I need to determine what causes this correlation to change as different explanatory variables change. Is there a way that I can regress ...
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12 views

nls model parameter compare

I am doing nonlinear regression using a same sigmoidal model for different treatments. for each treatment, I got a set of estimated parameters (a1, b1, c1 for treatment 1; a2, b2, c2 for treatment ...
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26 views

How to interpret prediction accuracy based on error analysis in test and validation sets?

I would like to calculate accuracy of my prediction model based on polynomial regression and I got some values for the test and validation errors 3.895 and 4.0125. I am wondering how these values for ...
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2answers
31 views

Should we report R-squared or adjusted R-squared in non-linear regression?

I am running a non-linear regression for a dose response with the equation: $$Y = \frac{c}{1 + \big(\frac x g\big)^b}$$ When reporting my results for publication, do I report the R-squared or ...
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35 views

Weibull fitting

I'm trying to fit a Weibull curve to my xy data. I know that the 3 Weibull model has 3 parameters, the scale, the shape and the location and I would like to estimate them from my data. I used curve ...
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1answer
33 views

intrepretation of ordered logit

I am trying to analyse my experimental survey results, where people are given one of two frames at random. 1.Gain is one of the frames. The dependent variable is the difference between whether ...
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0answers
16 views

comparison of N groups of independent individuals curves: summary-variables or nonlinear mixed effect model?

I want to assess wether there is a significant difference among two groups, based on a sample of independent individual curves in each group. The logical next step is to try to understand what ...
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22 views

Transformation of growth function with two pulses

I'm trying to linearize the following exponential growth function: $$ y = ae^\frac{t}{b}+(1-a) e^\frac{t}{c} $$ To preempt any question regarding why I'm doing this: I'm trying to regress this ...
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1answer
33 views

Nonlinear regression curve fitting doesn't work

I'm stuck with some seemingly easy task to fit nonlinear regression model. It worked normally until some new data came. Here is my code: ...
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18 views

Correlation between binary and categorical variables [duplicate]

what kind of correlation should I use in the case of having one dependent binary variable (has been to the doctor in the past few months) and one independent categorical variable, i.e, education?
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2answers
80 views

How does one perform multiple non-linear regression?

I performed an experiment where I took the heights of plants and measured a number of environmental conditions (air temp, soil temp, lux, air humidity, soil pH, wind) for each of those plants. I want ...
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0answers
19 views

General linear model ----How to improve the fitness?

I am doing the research of optimizing the signal integration high speed margin test parameters, and my goal is to find the parameters combination with the highest probability of "PASS". See the data ...
2
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1answer
34 views

Why such a dissimilar solution to logistic regression and linear regression?

In machine learning, linear regression and logistic regression are very common. The solutions to them are to find a parameter to minimize the energy function. Specifically, given a training data ...
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18 views

Is it possible to use stepwise linear regression to find the parameters that explain the most variation in the output of a nonlinear system?

I have a mathematical model of a system. We have to use a simulation software to check the response of the system to specific input signals or change of model parameters. The relationship between some ...
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27 views

Compare three non linear regression lines

I'm beginning to explore the world of the non-linear models and I'm needing to compare if there are significant differences between the slopes of three different groups. I have been reading some ...
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0answers
19 views

Linear regression with prior on $\arctan \beta_1$

Suppose we have $\hat{y} = \beta_1 x + \beta_0$ (I ask only for the univariate case.) A typical Bayesian approach might involve Normal priors on both parameters. I was thinking today about a ...
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0answers
14 views

Generating Confidence & Prediction Limits in Extrapolation of Non-linear Regression

I am using PROC NLIN/NLMIXED to estimate parameters from some equation and then trying to use these estimates in a different equation to generate out-of-sample predictions. The problem is when I am ...
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40 views

How to calculate uncertainty in bacterial growth rates (or in the slope of any local regression)?

I'm using a plate reader to measure optical density of different bacterial strains so I can compare their responses (growth rates and changes in them over time) to stress conditions. The growth curves ...
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0answers
15 views

Does R's NLS always fail if model parameters are not identifiable?

This question from several years back describes the "singular gradient matrix at initial parameter estimates" error. The answers say the reason for the error is that the parameters in the model are ...
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0answers
16 views

Comparing nonlinear models using the Chi-squared asymptotic approximation

I am attempting to identify the best model fit for a nonlinear mixed effects model using the asymptotic approximation to the Chi-squared test. When calculating the appropriate number of degrees of ...
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0answers
13 views

Determining fit for potentially periodic non-timeseries data?

I am working with genetic data that has 100,000 wide regions with given diversity values attached to them, as below: ...
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0answers
9 views

Non-linear Variables in Excel [duplicate]

Regarding the following equation in excel regression: y = x + x^(-.5) + e I have made the equation nonlinear in the sense that I added to the data a new column which takes the values of x to the ...
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0answers
27 views

About the Randomized Dependence Coefficient

In the paper The Randomized Dependence Coefficient, authors introduce a novel dependence coefficient which seem to be quite generic and powerful compared to what is present in the literature. It is ...
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1answer
9 views

Unable to predict using bart() {BayesTree}

I used bart function from BayesTree library to build a model on my training data. It fits my training data very well. However, I'm unable to predict for the test set and check its performance. ...
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0answers
8 views

Picking the Right Co-Variance

I am conducting a repeated measures regression, in a linear mixed model. I am also analyzing the data with a general estimating equation. The dependent variable is continuous (a measure of arousal) ...
2
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1answer
43 views

Fitting nonlinear meta regression models to data

I have a collection of data, obtained from different studies. To plot the ratio of means against different CO2 concentrations, I used a random effects model with a continues predictor (the CO2 ...
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2answers
253 views

nonlinear regression two equivalent models on paper, but different estimated parameters

I measured one response variable Y1 as a function of two measured independent variables X1 and X2 It is common practice in ...
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0answers
28 views

Nonlinear first-stage specification in 2SLS

My question is whether there are any substantial benefits from specifying a nonlinear first-stage in 2SLS regression. Generally, we assume that first stage is a linear relationship, like: ...
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0answers
57 views

How to know which model is appropriate for my data?

I study regional planning. there is a theory that says population density (D) is changing by distance to CBD (center of city). And the model for any city is different. And I have population density ...
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0answers
16 views

Transforming independent variables in R [duplicate]

Is there a way through which we can determine how can we transform our independent variables to increase linearity. I am aware of boxcoz function but it provides information on transforming dependent ...
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0answers
23 views

AIC for multiple nonlinear regression models

How do we got about using AIC for multiple nonlinear regression models ? For example: If i have a dataset with N instances, and they can be explained by a collection of 3 models where each model has ...
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0answers
95 views

Gini Coefficient - Variable Importance Measure

There is a whitepaper for selecting important variables in a linear regression model. The URL of the whitepaper is http://support.sas.com/resources/papers/proceedings15/3242-2015.pdf . It explains ...
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23 views

reason codes for non-linear models?

I have a non-linear model with n variables (ANN model). The variables are WOE-transformed to train the model. I have a test record scored using the non-linear model mentioned above and it is in the ...
0
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1answer
18 views

Testing the utility of adding a continuous variable to a nonlinear regression.

Let’s say I have the hypothesis that soil fertility affects the relationship between weed biomass and crop biomass. One way to go about testing that hypothesis might be to model the relationship ...
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4answers
237 views

How can I test a nonlinear vs a linear regression model?

I've got a panel regression model where the Ys assume a curved shape when plotted over time. A histogram of the residuals shows they are normally distributed but a residual-vs-fitted plot shows a ...
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2answers
56 views

multivariate mean?

[edit : because my question was ambiguous, I decided to rewrite it entirely, with some simplification but a lot more details on the experimental design] Four independent 10m*10m plots each received ...
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1answer
39 views

Assessing variable importance from coefficients and p-Values of linear regression

Is it correct to say that if the significance of a variable is very high (p<0.001) and the coefficient is very large that the variable is important in a general sense? If not can you give an ...
3
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1answer
43 views

OLS estimation for Nonlinear model

Consider the following model which may be nonlinear: $Y_{t} = f (X_{t}, \beta_{0}) + \mu_{t}, \hspace{0.2cm} t=1, ..., T$ If we assume that: $\mu_{t}$ i.i.d with mean = $0$ and ...
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1answer
50 views

What polynomial do I need for regression of such relations

I have following 4 graphs and for each I have to do regression. The relation is clearly curvilinear. What term should I use for regression (eg y ~ x+x^2) for each of these?
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1answer
254 views

Examples of Non-Linear Time Series?

Does anyone have an example of real world (ideally multivariate) time-series data that depends on its past in a non-linear, but additive way? I understand that there are several examples of ...
3
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2answers
60 views

Understanding Big/Little $O_p$/$o_p$ Notation for Estimators

I am reading a Text about Single Index Models (SIM), where a SIM is defined as $E[Y|X=x] = G(X' \beta)$, with $G$ and $\beta$ unknown. After proposing an estimator for the function $G$, the ...
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1answer
51 views

Visualizing nonlinear regression

I have following model using mtcars dataset: ...
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31 views

Methods for detecting nonlinear relationships among variables

I believe that some of my independent variables vary nonlinearly with my dependent variable. I know of a couple of ways to determine the possible type of function, but I'm wondering other methods, and ...
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0answers
73 views

Difficulty with logistic regression: logit transformation is non-linear

I am trying to perform a logistic regression to model likelihood of receiving a procedure given a certain diagnosis. There are several covariates to analyze but one of the main ones is patient age. As ...
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0answers
35 views

Interpreting GNM/GLM regression using R

I have a training dataset that contains input features. It's an input file which is tsv separated. I had input data for 200 rows with 4 cols. That last col is the target variable. I have also loaded ...
0
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1answer
61 views

Difference between SAS and R results - Nonlinear Regression

Hoping someone can assist with this rather niche question. I have a routine built in R for analysing depreciation curves, which is fit according to a logistic model with an additional additive ...
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0answers
37 views

Predicting time to failure with time varying cofators

The Goal I am modeling Hospital Length of Stay. More specifically, I would like to predict the number of days until a patient is discharged given all of the patients clinical factors throughout ...
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2answers
97 views

Regression analysis low R2 value - Result interpretation

When I run linear regression on my test data I get the following report: You can find the test data in here. The graph of actual vs predicted looks like: I would like to know if this is fairly a ...
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3answers
53 views

Hypothesis Tests for Non-linear least squares coefficients

I have a set of results that take the following form: ...
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0answers
14 views

Indicator regressions: standard errors

Hi I am estimating a regression of Y on X where both Y and X are indicator variables, that is, they take values 1 or 0. The model is $Y=\beta*X+\epsilon$ (without constant). I use OLS to estimate the ...