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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13 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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0answers
21 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) [on hold]

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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0answers
22 views

nonparametric estimation to similar shapes with different mean and variance [closed]

I have several counting datasets. The distributions' shapes are similar, but their mean and variance (scale) are quite different. Is there any method to estimate these datasets? What I need is a ...
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1answer
113 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 ...
2
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0answers
16 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. ...
2
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1answer
38 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 ...
3
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0answers
13 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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23 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
35 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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45 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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0answers
21 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 ...
0
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1answer
31 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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0answers
13 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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0answers
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
33 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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0answers
18 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
65 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 ...
6
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3answers
227 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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0answers
33 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
97 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 -- ...
3
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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 ...
0
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0answers
32 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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0answers
49 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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13 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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4answers
331 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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11 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
46 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
32 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
412 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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38 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, ...
2
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0answers
27 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 ...
0
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0answers
59 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 ...
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0answers
49 views

Fitting logistic function in R, response unconstrained to 0 < Y < 1

I want to fit a logistic function of the form $$f(t) = \frac{C}{1+ab^{-t}}$$to some data that I have, using R. There is some uncertainty to $f(t)$, and its ...
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0answers
21 views

How can I make use of correlations between datasets for building multiple models?

I'm building models for a bunch of spatial points. Linear regressions models, for now, but I will have expand to more complex ones (non-linear, time-series models, etc.). So far, I've looked at the ...
7
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2answers
254 views

Is there a way to force a relationship between coefficients in logistic regression?

I would like to specify a logistic regression model where I have the following relationship: $E[Y_i|X_i] = f(\beta x_{i1} + \beta^2x_{i2})$ where $f$ is the inverse logit function. Is there a ...
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86 views

Alternatives to Non-Linear Regression

I'm not a professional statistician but I frequently work in the area of data analysis using R and Python, and frequently use linear regression models (OLS) or quantile regression, and tree based ...
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0answers
38 views

How do I compute for the utilities in a choice based conjoint analysis?

I want to learn how to compute the utility value or estimate part-worths of the individual attributes in a conjoint analysis. Is there an equation to help me figure it out? All I see are software ...
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0answers
19 views

Logistic regression model [duplicate]

Does one always have to standardize all coefficients in logistic regression models? Also does matlab automatically standardize coefficients or does this have to be done by the user? Thanks for any ...
1
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1answer
45 views

Estimate of Coefficient Variance in multiple regression

I'm trying to compute an estimate for the variance of the estimated coefficients in a non-linear regression using the formula described in link. I can't figure out how to build $F_{ij}$ Let's ...
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0answers
118 views

Is there evidence of mediation? Need help with interpretation of mediation analysis results

I have performed a mediation analysis. I have an independent variable T, a mediator M, and outcome Y. (All 3 variables are binary, and I use logit.) (While I used Stata ...
0
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2answers
96 views

Non-linear regression models

If my data is non-linear (assume it follows a quadratic function), how should this be handled using regression? Should I run a regression against the polynomial function or attempt to transform the ...
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0answers
10 views

Non-linear auto-regressive model - preselection of relevant columns

Let us consider a dynamic system with nonlinear auto-regressive evolution such as $$ x_{t} = f(x_{t-1},x_{t-2},\dots,x_{t-d})+\epsilon_t $$ where $x_t\in\mathbb{R}^n$ is vector and $\epsilon_t$ is a ...
3
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1answer
64 views

Need an Introduction to Generalized Non Linear Multiple Regression

I have been searching the internet for a generalized method for doing regression analysis on non linear data. My model can be represented as $$Y = \beta_0f(X_0) + \beta_1g(X_1) + ... + \beta_nz(X_n) ...
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0answers
22 views

Small sample size : dealing with bootstraping for linear or nonlinear multiple regression

I am wondering to heal my ignorance from your experiences or your modeling knowledge. I have many matrices of quantitative variables, let me start with three matrices of proportions.To express ...
0
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1answer
73 views

When should I use nonlinear-regression model

I have the following table: ...
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0answers
20 views

fitting a non-linear curve with one parameter

I have an equation: $\ddot{x}+(\delta+\epsilon\cos{t})x=0$ known as the Mathieu equation.The $\delta-\epsilon$ parameter space of this equation looks something like The red lines in this diagram ...
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63 views

Syntax error when fitting generalized non-linear model with gnm

I am trying to fit functions to generated data using nms. I don't have much experience fitting these models. The data is binomial which is why I'm using nms instead of nls. First I want to generate ...
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26 views

If we nonlinearly transform the LS estimates, will they still be unbiased estimates of the true value?

So this is an discussion which came up with a friend/colleague who is a physicist postdoc. He has a bunch of data $(x_i,y_i)$ and wants to fit it to the form $y=e^{ax}$. He uses (weighted) nonlinear ...
3
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1answer
79 views

nonlinear meta-regression

Can someone point me to a basic explanation of theory and methods for fitting nonlinear curves (particularly quadratic functions) to meta-analytic data? I have a set of effect sizes that are clearly ...