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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How assess model fit for non-linear regression?

I am looking at non linear regression. Below is some example output from a non linear regression using MATLAB. There are also two links below this output from the Minitab website. The links explain ...
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8 views

Genetic algorithm for parameter estimation in nonlinear model [on hold]

I use Genetic Algorithm function in GA package for parameter estimation in nonlinear model. I use a simulation data, which all of the variables have multicolinearity problem. When I use GA function, I ...
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29 views

F-test to determine whether more than two sets of data differ

Here is the context for my question: I understand that you can fit the same model to two different datasets separately and then fit the model to the datasets pooled together as a way to discern ...
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49 views

How to plot the confidence interval from boot.ci output of nonlinear regression in R?

I have a data.frame with two columns (x and y) for which I have obtained a nonlinear least squares fit: -a/(b+exp(-x)). Now I'm trying to plot the 95% confidence interval for y. My best attempt so ...
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29 views

Which type of Regression model do I need and what do I need to do to my variable to allow it to work?

thanks for taking the time to read this! A little background, I'm pretty enw to doing most statistical analysis; I've only ever done linear regressions and I tried doing research online but was ...
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MATLAB: bounding the parameter values in nonlinear modelfitting and AICc scores

I am trying to fit a number of nonlinear models to a dataset, and I need to bound the model parameter values to all be positive. I tried lsqcurvefit function and it works. However, I also need AICc ...
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1answer
35 views

Consequences of violating assumptions of nonlinear regression when comparing models and/or datasets

I have a question about the consequences of using non-linear regression when the data violate the assumptions of (1) homoscedasticity and (2) normal distribution. Specifically, I am wondering about ...
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18 views

Neural Network Learning Curves with Low Test Set Error

TLDR: You can see my neural network learning curves here: http://imgur.com/0CL6LVY. Which regularization term would you pick given that the test error actually drops below the training error at some ...
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50 views

How to fit an exponential equation of the form $Y = A + Be^{CX}$ to data

I need some assistance with a nonlinear adjust. I am trying to make a mathematical model that describes the rate of silicic acid escaping from an underwater sediment. For theoretical reasons, the ...
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2answers
90 views

Why do I get linear model when I tried to fit exponential model?

I was wondering why do I get linear model when I'm using exponential model, y = a * exp(-b*-x), to fit my data. Here is my code: ...
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29 views

Confidence interval of the mean response from nonlinear model

My problem (question at the end) is to calculate confidence interval (CI) (NOT prediction interval) of the response of a nonlinear model. I am working with R but this question is not R-specific. I ...
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29 views

piecewise linear regression with unknown number of knots

I have a model that depends linearly on $v$ and $\alpha$, but not linearly on other two parameters $T_0$ and $T_1$: $f(i; v, \alpha, T_0, T_1)$. Using least squares, I can solve for $v$ and $\alpha$, ...
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1answer
33 views

can I apply loess or spline regression in mixed model?

My situation right now is that I have the mixed model with quadratic term but it doesn't perform very well. So I am wondering if I can apply loess or spline regression to the mixed model instead of ...
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38 views

How to fit a two phase exponential decay curve?

I have a model where the variable y theoretically should have an exponential decay over time x. The real data showed a fast decay to begin with and a slower decay towards the end. Here is the code: ...
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11 views

MARS Modelling for large no of variables

I have data with more than 200 predictors, can MARS be used for such a data? Objective is to identify predictors which are most important across each category. So these 200 predictors are from 6-7 ...
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90 views

Calculate PLS Xscores for predicting new data

I wish to extract Partial Least Squares (PLS) components to apply non-linear regression (Gaussian Process Regression (GPR)) on the scores of the predictors (Xscores). The reason is my data is very ...
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20 views

Multivariate quantile regression

I have a multivariate linear model: $\mathbf{Y} = \mathbf{X}\mathbf{B} + \mathbf{U}$ where the matrix $\mathbf{Y}$ represents stock returns, the design matrix is constituted by some explanatory ...
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1answer
16 views

MLP with 2 outputs vs 2 MLPs with single outputs for nonlinear regression

Assume i want to apply nonlinear regression to two output variables with multilayer perceptrons. Is there difference between using a MLP for each regression with single output and using a single MLP ...
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41 views

Can I use deviance to compare the fit of a model to different datasets?

I'm using R's nls to fit different datasets to the same model. I've read that using R-squared is usually not correct for ...
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26 views

Reverse-engineering a (custom goods) pricing algorithm - each db row has: | 3 factors | 2 co-variates | price | (I have over 100k rows of data) [closed]

just wanted to mention up front that my question doesn't concern dynamic pricing, price optimization, revenue management, etc. No time series analysis either. It's just a simple multivariable ...
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1answer
128 views

Deep neural nets, RELU's removing non-linearity?

are RELU (Rectified Linear Units) activation functions considered non-linear? They are linear when the input is > 0 and from my understanding to unlock the representative power of deep networks ...
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0answers
17 views

How to measure the degree of nonlinearity in regression model [duplicate]

Could anyone guide me on how can we measure the curvature of nonlinear models? I have to know the methodology to measure nonlinearity (both intrinsic and parametric) for nonlinear regression model. ...
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1answer
45 views

Stability of univariate fractional polynomial models

I can't decide what is the best way to assess the stability of a higher order fractional polynomial model. To use an example I have been working on, I am analyzing a dataset with panel data selected ...
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14 views

Multiple comparisons of parameters from non-linear regression

Hei, I want to compare parameters a_i and b_i estimated by nonlinear regression (y=a_i*x/(b_i+x)) for different data-sets (let's say 8 different data sets). I have calculated the non-linear ...
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25 views

How to pool mice results from piecewise regression

I'm trying to find breakpoints using the segmented package. As there are some missing values I would like to use mice for imputing these. Unfortunately I'm clueless ...
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1answer
39 views

Pitfalls in Fitting Nonlinear Models by Transforming to Linearity

Some nonlinear models can be transform to linear models. My understanding is that there might be one-to-one relationship between the estimates of nonlinear model and its linear model form but their ...
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54 views

lm and nls F test in R

I am trying to compare a linear model and other non linear models(Asymptotic, Logistic and Ricker) by means of an F test or a likelihood ratio test. I have tried anova(Linear, Logistic,Ricker, ...
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26 views

Confidence intervals for a curve with bootstrapping

I am estimating y= az + f(x) in a semi-parametric way. I want to compute the standard error for the estimated coefficient for a ...
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1answer
34 views

Non-Linear regression that captures jumps and an exponential decay

I have some data that has the pattern in the picture below (but little noisier than that). I want to run a non-linear regression that tries to capture the dynamic of this data in the time-series ...
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15 views

use of the hessian when minimizing sums of squares in non-linear regression model

Hi: I am using numerical optimization to minimize the sum of squares a non-linear regression model. I've done lots of checks with various algorithms and I use analytical derivatives so I'm confident ...
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8 views

Interpolating singular values

So I have the singular values associated with a data matrix and I would like to interpolate them and then find the maximum curvature of the interpolation in order to decide how many singular values to ...
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0answers
35 views

Nonlinearity in OLS-models

I have a question connected to the OLS-Model's assumption of Linearity between parameters. What should be done if the assumption is not fulfilled? My second question is if I can use multinomial ...
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22 views

Nonlinear form of ANCOVA?

I would like to compare a control group against a test group using something like ANCOVA. However, the covariates are not simple, as some items may have already been increasing with time, others ...
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2answers
76 views

Creating groups using two continuous variables without using median-splitting?

I have two continuous variables, one of individuals' retrospective childhood anxiety and another regarding their current level of anxiety. Research has demonstrated that during a snapshot of ...
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3answers
262 views

Deciding between a linear regression model or non-linear regression model

How should one decide between using a linear regression model or non-linear regression model? My goal is to predict Y. In case of simple $x$ and $y$ dataset I could easily decide which regression ...
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48 views

How to find p value for trend in a Proportional Hazards Cox regression model?

I am running an analysis using a Proportional Hazards Cox regression models. My main interest variable is categorized and I find a significant effect only on medium category. I would like to see ...
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1answer
206 views

Plotting a polynomial regression with its confidence interval of 95% in R

I have been trying for a while plotting a polynomial regression using R. I have read several libraries, as ggplot2, qplot, etc, with no succeed. The next are my data: I normally use the R GUI called ...
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11 views

Does Prism use smoothing to calculate a non-linear fit to data?

I have some read out vs. concentration of an agonist. I calculated EC50 using Prism6. My method was pretty simple. Log transform concetrations. Fit the data using log(agonist) vs. response -- ...
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1answer
69 views

Designing Asymmetric regression (assymettric loss for regression)

I have a hybrid classification/regression problem.The predicted value can be assumed to be centred around 0. I want to penalize the predictor more, if the predicted value and actual value have ...
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38 views

Deforestation Scenarios using Logistic Regression (Stata)

I used Logistic Regression to model the contribution of a range of explanatory variables on deforestation processes (being my dependant variable - Deforested=1, No Deforestation=0) in the Brazilian ...
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59 views

How to estimate parameters of a nonlinear function with log-normal error?

Consider you have some nonlinear function \begin{align} y_i&=\epsilon_i f(\beta,x_i) \end{align} where $\epsilon_i$ is log-normally distributed with mean 1, and \begin{equation} ...
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14 views

Non-linearity in a general framework [closed]

What is the best way to show the effect a variable has on an outcome variable? For example, is the effect of X on Y linear or non-linear?
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378 views

What are the formulas for exponential, logarithmic, and polynomial trendlines?

In creating linear trendline, I used the following formulas: $$y=mx+b$$ $$m = \frac{n\sum(xy)-\sum x \sum y}{n\sum x^2 - (\sum x)^2}$$ $$b = \frac{\sum y- m \sum x}{n}$$ and this for the R-squared: ...
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12 views

Intrinsic topology and metrics… (looking for name of a method)

Suppose I have an n-dimensional dataset and its points are roughly in the shape of an n-dimensional horseshoe or something along those lines. Using euclidian distance might be a bad idea, since points ...
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1answer
48 views

Confidence interval in a nonlinear model

Thanks for your suggestions.Actually i have the following model that i explains to you. Suppose i have observations structure like $$\begin{align} y_1 &=&v_1+e_1 \\ y_2 &=&v_2+e_2 \\ ...
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1answer
37 views

Fitting non linear regression with coefficients in the form of polynomial with Levenberg Marquardt

I am trying to do non-linear regression by using Levenberg Marquardt least square fitting (in R). I know that it can do the fitting for a function in the form of $f(x) = sin(Ax)+cos(Bx)$ to ...
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3answers
438 views

What are criteria and decision making for non-linearity in statistical models?

I hope that the following general question makes sense. Please keep in mind that for the purposes of this particular question I'm not interested in theoretical (subject domain) reasons for introducing ...
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44 views

Ordinal Regression- multiple continuous predictor variables

I am working on a project where I have a dependent variable that is ordinal, and two continuous independent variables. I believe running an ordinal logistic regression is the proper method of attack, ...
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33 views

Statistical tests to compare sigmoidal regression equations

Data from my experiments (sample shown below) can be fitted using a sigmoid function. The equation I used to fit the data is: y = A2 + (A1-A2)/(1+(x/x0)^p). Each experiment yields data (and a ...
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78 views

Nonlinear mixed effects model proportion data

I'm working on proportion data (clutch success: number of hatch eggs over total clutch size) which is non normally distributed. I would like to fit a nonlinear mixed effects model with 6 fixed effects ...