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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14 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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35 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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16 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 ...
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2answers
210 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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72 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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13 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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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 ...
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1answer
30 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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70 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 ...
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2answers
82 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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8 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 ...
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1answer
50 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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16 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 ...
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1answer
70 views

When should I use nonlinear-regression model

I have the following table: ...
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0answers
13 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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33 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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0answers
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 ...
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1answer
56 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 ...
3
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2answers
272 views

Analyze scatter plot

I want to study the relationship between two variables. I've got the following scatter plot. But now I'm hesitating on what to do with this: Should I check the assumptions of OLS and then use the ...
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33 views

nls standard deviation calculation

I have fitted a non linear assymptotic equation to a set of data and my interest is in getting the standard deviations of the fitted parameters. Is this possible in nls?
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52 views

Error in gnls step halving factor

I am getting an error running a gnls() on some data I have. I was able to converge using nlsLM(), but I ran into some autocorrelation in my errors, so I want to try to use gnls() so that I will be ...
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1answer
110 views

ARIMAX with a specified nonlinear model using the arima function in R

I am interested in fitting an ARIMAX model using R. As known, ARIMAX can be understood as a composition of ARIMA models and regression models with exogenous (independent) variables. I have a time ...
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1answer
53 views

Is the random forest solution for regression interpretable and sparse?

I have a regression problem scenario. Basically, I want to model a certain biological problem with regression models and at the end my model should be interpretable. I need to have a sparse model. So ...
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1answer
23 views

Cross-validation for nonlinear models that are linear in the parameters

I'd like to know if it's correct to the CV function in the forecast R package (http://cran.r-project.org/web/packages/forecast/forecast.pdf) to cross-validate a nonlinear model that is linear in the ...
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55 views

Trouble fitting mathematical model to data in R

I am trying to select the correct mathematical model for my standard curve. This data was collected from spectrophotometry. I am hoping to get a model to help me detect very small absorbance. ...
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64 views

NARX model to predict future values

I have this problem , where I have to predict a value of a indicator which depends on 270 other predictor variables. I read the time series modelling and prediction on MATLAB , which took the example ...
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49 views

creating a equation for non linear multiple regression to predict a value based on the inputs given in excel

I have data with 5 columns namely Botany,Zoology,Chemistry,Physics and Rank in a excel sheet . The data here is non linear . So I want to generate a equation in the form of y=a+bx1+cx2+dx3 In ...
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57 views

Pareto two-tailed GLM regression

How can I perform a Pareto two-tailed GLM regression? Any reference to link functions and code in R?
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1answer
61 views

What is the difference between GLM and splines?

Suppose we want to predict $Y$ given the following $X$ observations: ...
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2answers
127 views

Estimating “Probability” in normal probability plot

I plotted normal probability plot in R using qqnorm and qqline. I want some help on: How to estimate "probability" that a data ...
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36 views

Selection of failed fitting results in MC Simuation

I recorded a set of experimental rates $r = r(c,T,P)$ at 2 values of $c$ and >15 values of $T$. $r(c,T,P)$ obeys the following functional form: $$ r(c,T,P) = ...
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31 views

'systemfit' package and systems of non-linear equations/regression

I am trying to estimate a system of non-linear equations using 'systemfit' package in R. I have had issues with it. The two equations share the same parameters i.e. "sigma", "al" and "ae". I expect ...
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2answers
82 views

Linear post-treatment of nonlinear regression

I have often found in practice, using nonlinear regression techniques such as feedforward neural nets or random forests, that the resulting actual-vs-fitted plot (on training set) seems obviously ...
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8 views

Function domain as a problem for linear output unit

I'm doing some regression using neural net(using MLP implementation from http://deeplearning.net/tutorial/mlp.html, I used my own but it produced the same results before I opted for this one), ...
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2answers
75 views

Non-linear least absolute deviation regression with multiple global minima

I am fitting a single exponential decay formula with three parameters (a,b,c): y ~ $a \exp(-xb) + c$ using the LAD cost function: $ \min \sum |(y - f(x))| $. $x$ is in units of time (as is $b$), and ...
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22 views

hierarchical logistic regression Block non-significant, interaction significant

I'm using hierarchical logistic regression and having some difficulty. Im trying to predict self-harm vs none based on IVs age, gender, alcohol, educational attainment. They are all yes/no except ...
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3answers
492 views

What does “curvilinear” mean?

As far as I can tell, curvilinear is defined vaguely but means the same as nonlinear. Is that correct? Or does curvilinear have a distinct definition?
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33 views

Beyond multiple linear regression for longitudinal data?

I have a relatively large dataset from a longitudinal study (~100k subjects and ~10 random effects) where the outcome is a real-valued parameter. A simple run of R's ...
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1answer
64 views

How to compare different nlme models ?

If there are 2 nlme models with same non-linear mean function, model 1 and model 2, how do you compare them ? Which R function does this for us ? And when there are random effects or fixed effects, I ...
2
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1answer
19 views

Varying Non-Linear Parameters Based on Groups in R

I'm trying to develop a non-linear model, but I'd like to have the values for the parameters vary by group. To give you an example, a section of my data (just random numbers here) looks like: ...
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1answer
115 views

Model with non-linear transformation

I don't understand this concept well and need help. I was choosing whether to use a linear model or apply a non-linear transformation in my model formula. To do a diagnostic, I quickly plotted my ...
2
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1answer
91 views

Choosing variable transformations in non-linear relationships

I am confused about how to apply a transformation to my predictor/response variables to test curvilinear relationships. I read about log transformations, polynomials, quadratic functions. But I am not ...
3
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2answers
107 views

Good machine learning algo for partial derivatives?

Does anyone know of good robust algos to estimate partial derivatives of a regression model? I am talking about a general regression model like this: $\mathbb{E}(y|x_1, x_2, ... x_n) = f(x_1, x_2, ...
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0answers
24 views

how to implement linear or non linear regression for 3d position estimation?

I am a beginner in Machine Learning. For my project I need a regression algorithm that can estimate the 3D position of a device based on some constraints (moreover inputs). I know how to implement ...
2
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2answers
164 views

R: Fitting a model with periodic, nonlinear and categorical components

Can anyone give me some advice on how to fit a model with linear (some categorical), non-linear and time series components in R? I don't want to use a non-parametric model like a Loess smooth or ...
2
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0answers
44 views

Catagorical variables with very uneven distributions? Removal/modify/leave?

In my current dataset I have quite a few categorical variables. Most have decent distributions between the categories. 30:40:30 splits etc. where these are percentage of dataset members per category ...
3
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2answers
47 views

What model would be appropriate for predicting electrical consumption given multiple (mostly) independent variables?

I have about 1000 samples worth of daily electrical consumption for a building. I'd like to build a predictor based on a number of observable inputs, including: daily temperature (continuous) hours ...
3
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1answer
41 views

Fit nonlinear parameter

I'm attempting to fit this model: $P = C_0 + C_1*U^r$ Given known vectors of observations $P$ and $U$, I want to fit values for $C_0$, $C_1$ and $r$. How do I make this fit in R? or preferably GSL ...
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2answers
27 views

Can time be squared to develop a curvilinear model of crop yield against time?

I am developing a linear model of yield against time (33 years of yield data) where year is 1975,1976....2007. I want to know whether change in yield over time was linear or not. So I fitted a linear ...
3
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1answer
150 views

N-sigma curves for a non-linear least square curve fit

I'm using python's scipy.optimize.curve_fit routine (which uses a non-linear least squares) to fit an exponential function of the form: ...