Tagged Questions

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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16 views

Mean square error in log-linear model

Let's consider the following log-linear model: $log(Y_i) = \alpha + X_i\beta + \epsilon_i$ for i = 1, ..., N The fitted value is: $\widehat{log(Y)} = \hat{\alpha} + X\hat{\beta}$ Assuming ...
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1answer
24 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
51 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
76 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
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 ...
3
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1answer
43 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
13 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
69 views

When should I use nonlinear-regression model

I have the following table: ...
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0answers
9 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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0answers
29 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 ...
2
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0answers
22 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
49 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
253 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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0answers
28 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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0answers
37 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 ...
1
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1answer
90 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 ...
0
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1answer
32 views

Does the randome forest for regression solution are interpretable and sparse?

I have regression problem scenario. basically I want to model a certian biological problem as regression models and the end my model should be interpretable. I need to have sparse model. so I'm ...
2
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1answer
21 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 ...
3
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0answers
51 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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0answers
43 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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0answers
36 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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0answers
40 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?
0
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1answer
59 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
93 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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0answers
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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0answers
25 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 ...
3
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2answers
76 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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0answers
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), ...
3
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2answers
64 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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0answers
16 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 ...
7
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3answers
442 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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0answers
31 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 ...
0
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1answer
56 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: ...
4
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1answer
109 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
85 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
99 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, ...
0
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0answers
22 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
159 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
44 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
40 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
votes
1answer
113 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: ...
1
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2answers
78 views

Multiple regression analysis with spatial data as independent variable

In my PhD thesis I am working on spatial modeling of different chemical parameters in groundwater, and for spatial modeling I am also using the multiple statistical approach. I have a question about ...
4
votes
1answer
249 views

Residual plot for nonlinear regression

I have a couple of questions regarding performance of nonlinear regression models. Are the residuals from a nonlinear regression model supposed to be randomly distributed too (as in linear ...
2
votes
1answer
15 views

Error on extrapolated values from a fitted function

I have some data points and I fitted a function (2nd order polynomial here) to the data. The algorithm (scipy.optimize.curve_fit) gave me the optimal parameters and ...
-1
votes
1answer
60 views

Why can certain variables in a multiple regression not be included in logarithmic form?

I have a multiple regression equation where log(salary) = b0 + b1(ceotenure). What is the purpose of putting the dependent variable in logarithmic form? How would you interpret the change in y for a ...
6
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1answer
245 views

Nonlinear regression

I have some functions of $x$, in the form of $d\sqrt{x}$ or $d\log(x)$ where $d$ is known. I would like to rewrite (approximate is fine) them in the form $a/(1 + bx^c)$, where $a$, $b$ and $c$ are ...
1
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1answer
76 views

$R^2$ correspondence for nonlinear time series

Is there a statistical measure for nonlinear time series data that is comparable to $R^2$ value in linear regression (giving an idea of how well the fit is)? The data is not monotonic, so I cannot ...