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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Why is my high degree polynomial regression model suddenly unfit for the data?

I'm building a ridge regression model in scikit-learn and trying to find the optimal degree polynomial to use. The data I'm working with is a fairly predictable time series of hourly traffic volumes, ...
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2answers
50 views

How to reduce the number of labels in regression

I'm working in a regression problem, related to bio-signals, where my labels are integer numbers between 0 and 10. I've tried a couple of regression algorithms already, mainly linear regression. Edit:...
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8 views

How to deal with model misspecification - linktest

I am running an OLS model to examine to what degree is the physical quality of life (SF-12 scale) is associated with depression (HADS scale), adjusting by age and the presence of an acute illness (yes/...
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1answer
21 views

How to reduce variables in logistic regression?

I am running a logistic regression to predict Yes/No. I have more than 200 independent variables. I have tried to input all the variables, the result is terrible. It is obvious that one variable will ...
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2answers
65 views

Confusion about when to use least-squares regression analysis

I am going through an article titled On the misuse of regression in earth science. On page 65, the author say as follows about the least-squares method. It is usual to require that the ...
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14 views

Macroeconomic Variable in Probit Logit Model [closed]

I am estimating a Logit Model in STATA 13. I have an Enterprise data set 2014 collected for 1000 firms. Some of the variables are in continuous form whilst others are binary. I am using Excel to input ...
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26 views

How to decide a model for my logistic regression?

suppose i have a data set containing 9 variables/features (x1 x2 x3 ....x9) and thus resulting into formation of matrix X of dimension (m*9), i have a discrete output matrix(Y) containing binary ...
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14 views

How to estimate the goodness of fit in a non linear regression?

I have made a non linear regression, and when I run an ANOVA these are my results, How can I calculate the R2 or another goodness of fit with these results? Thanks!
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1answer
50 views

model for non-linear data with repeated measurements

I have to do a model for non-linear data with repeated measurements. I worked with predatory insects. I did an experiment with 4 treatments, where per each treatment predators received a different ...
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1answer
48 views

How does a LOESS model do its prediction?

I understand the theory behind LOESS, but how does it do prediction without coefficients? I'd like to use LOESS prediction, but need to be able to explain it.
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50 views

Nonlinear transformation using the beta distribution

I'm trying to estimate the following equation (abstracted from this paper) in Matlab: $y_i=a+b\frac{(x_i-min(x))^{(c-1)}(max(x)-x_i)^{d-1}}{B(c,d)(max(x)-min(x))^{c+d-1}}+\epsilon_i$ where $B(c,d)$ ...
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27 views

Linear or non-linear model for social interaction with R

The question here is whether the cooperation of people with equal or similar abilities leads to better results than the cooperation of people with different abilities. The setting is a group of ...
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3answers
36 views

what makes neural networks a nonlinear classification model?

I'm trying to understand the mathematical meaning of non-linear classification models: I've just read an article talking about neural nets being a non-linear classification model. But I just realize ...
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20 views

weighted stdev or quantiles to show variation

I have data in the "dat" vector and I am looking to report the weighted mean and also some information on the variation of that mean. As a toy example you can see the data in the "value" vector and ...
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0answers
27 views

Nonlinear Multiple Regression

I have a dataset that has multiple x predictor values. To fit a model, I was going to use multiple regression but I looked at the scatter plots for each x value and the y dependent variable and they ...
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15 views

Curve fitting of Abs(A+M0*(1-2*B*exp(-t/T1)))

I apologize for the less-than-descriptive naming of this post, but I could not think of what this kind of function was called. I am trying to fit MRI T1 relaxation time to a curve: $M(t)={\rm abs}(A+...
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19 views

Regression or fit with an homographic or a linear fractional relation

This question is motivated by exploratory data analysis. I have a number of variables, related to a chemical reaction. Each variable is the quantity of a chemical species produced in different ...
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13 views

Using nlsLM() for importance sampling for pricing european optoins

I am trying to implement a method for finding an optimal drift in pricing European options with importance sampling using this article. The article in pages 489-490 suggests to use Levenberg-...
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2answers
46 views

Finding correlation between nonlinear variables sets & forecasting

I have two data sets. Data Set A is % over/under budget for a list of non-related projects. Data Set B is % over/under time for the same list of projects. Here is a sample of the data Will I be ...
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30 views

Machine Learning: Non-Linear Regression over dataset with very similar predictors and very different targets

I have a time-series dataset collected by a group of biologists counting the abundance of a particular animal species in an area. I later enriched this dataset with weather variables (e.g. temperature,...
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24 views

Machine Learning: How to solve “class imbalance” in Regression Algorithms?

I have a time-series dataset collected by a group of biologists counting the abundance of a particular animal species in an area. I later enriched this dataset with weather variables (e.g. temperature,...
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0answers
36 views

Estimating data set size for pattern extraction

I have a dependency treebank comprised of 100 structures, which is divided into a training set and a test set. I extract some rules ((DS,PS) pairs) to convert the treebank to phrase structures. When I ...
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1answer
49 views

Can we use bootstrap samples that are smaller than original sample?

I want to use bootstrapping to estimate confidence intervals for estimated parameters from a panel dataset with N=250 firms and T=50 month. The estimation of parameters is computationally expensive (...
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1answer
43 views

Good text on nonlinear regression (M.S. graduate-level)?

I've covered a linear models sequence where the classes discussed linear models using matrices, covering various experimental designs (split-plot, for example), ANOVA using matrices, and ending with ...
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1answer
247 views

Regression when response variable is a function

I have a set of data $(X_i,Y_i)$, $i=1,\ldots,n$ where $X$ and $Y$ are supposed to satisfy the following equation $$ y = \beta_0(1+x^2)^{\beta_1},\quad x>0, \quad\quad (1) $$ I am interested in ...
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35 views

Non-convergence in nonlinear regression

I've been studying a manuscript from the chemistry literature (not mine) that resorted to a trick to obtain convergence of a non-linear model fitted to experimental data. They wanted to estimate a ...
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24 views

Non-linear least squares and the distribution of an estimator

I have been trying to find the asymptotic normality of the non-linear least squares estimator. If I start with $0=X_t(\beta)'(y_t-x_t(\beta))$. I know that I have to perform Taylor expansion around ...
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12 views

Estimating covariance matrix from multiple distance measurements

I have a setup that can measure the distance between two beacons. The first beacon is aware of its 2D location and is moving around while measuring the distance to the second beacon. I've setup a ...
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0answers
31 views

Circular regression- R-Squared Value

Just like we have $R^2$ in linear regression, How do I find out the 'goodness of fit' of a circle to a given data? Is it wrong to use the $R^2$ formula from linear regression, $R^2 \equiv 1 - \frac{...
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2answers
105 views

suitable non-linear equation to capture a 'J-shaped' relationship between x and y

I am trying to model the relationship between forest age and individual tree mortality rate. The probability of mortality declines rapidly as forests go from being very young, and then creeps back up ...
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1answer
60 views

Fitting a nonlinear regression $Y=1 - a^{-bx}$

I have the following dataset: where X:Y 1:0.81 2:0.86 4:0.9 6:0.93 8:0.96 10:0.98 12:0.99 14:0.99 16:1 18:1 20:1 ..:1 Since the limit of the regression ...
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0answers
16 views

Validating regression - common and best practice

Is there a reference setting out a best practice way to validate a regression (such as Lasso, but in general any automated regression), and what is done in practice? My motivation for the question is ...
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16 views

How to relate distributions?

I have 100 objects. Each object has 10 (highly correlated) attributes that I can measure. For each object, I obtain 10000 samples of that object's attributes. I now want to relate the attributes ...
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11 views

Why doesn't the logistic regression model include error? [duplicate]

I know it comes from the fact that y is a vector that only has binary values, but I'm looking for a better explanation...
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1answer
41 views

What the interpretation when both the non-squared and squared term are significant?

I have a logistic regression model and added for a curvelinear effect both the non squared term and a squared term to the regression model. They are however, both significant. How do i interpret this?
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2answers
47 views

Help interpreting interaction terms in proportional cumulative logistic regression- ordinal regression

I am using the polr() function in R to analyze the relationship between a students score on their first exam, their score in their prerequisite course, and their beginning of semester GPA on their ...
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31 views

Which non-parametric multiple-regression methods are computationally efficient with respect to the number of regressors?

I did some regression in R with random forests and got some decent results, $1-\sum{|e_i|}/\sum{|y_i-\bar{y}|}=0.692$, but I want to do better than this. Through my research, I have concluded that the ...
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2answers
55 views

How to interpret Quadratic Terms

I'm answering a practice exam questions, and having trouble with one on quadratic terms. Could someone give me a quick summery of 1) why they are sometimes included? 2) How to interpret them? In ...
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1answer
48 views

Non-linear function optimisation using nlminb function in R

I have been getting error messages in my attempt to estimate parameters in a non-linear function using nlminb function. The following is the code: ...
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1answer
38 views

Can nonlinear regression with least squares estimations be used for testing hypotheses with data containing dependent observations?

I counted the number of animals of a certain species in 6 fixed locations on a monthly basis for 18 months. I now would like to test the effects of location, starting density, and time on the dynamics ...
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13 views

dependent variable in shares, independent variable log transformed

I havea question. My dependent variable is in percentage (shares of renewables in total energy supply). Hence, my variable is bounded but values are not closed to the bounds. My professor told me that ...
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0answers
40 views

Nonlinear regression vs. GLMs for estimating ED50

Are binomial GLMs better than nonlinear regression for model-fitting, and predicting ED50s and other effective dose point intercepts? In toxicology it is typical to run an experiment with a ...
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31 views

Significance testing between two hyperbolic curves

I have two curves for biological data (one-site binding). These curves were both fit using the following (Michaelis-Menten) model: BRET2 = (Bmax * RFU_RLU)/(Kd + RFU_RLU) Note: (x,y) here is ...
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0answers
15 views

How to assign defined training set, val set and test set for training a Neural net in NNtoolbox?

To find an optimal number of hidden neurons and layers in my code using feedforward net, I use cross validation technique and cvpartition function to split data. Now my aim is to use this split data ...
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2answers
81 views

Compare MLR model to model $Y_i = (\beta_0 + \beta_1x_{1i} + \beta_2x_{2i} + \epsilon_i)^{\beta_3}$?

If I have theoretical reasons to suppose the data might be fit with an unusual equation such as the following: $$Y_i = (\beta_0 + \beta_1x_{1i} + \beta_2x_{2i} + \epsilon_i)^{\beta_3}$$ Can I use ...
1
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1answer
36 views

How do you do a non-linear Poisson? What even is it?

I have a count data that I am having trouble transforming to be linear. First, what are smoothing functions and how do I do it in R? Let's use the famous crab satellite example. If you plot width to ...
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11 views

How are the values of knots in MARS calculated?

I'm wondering how the MARS algorithm decides on the specific values for the knots which are included in the hinge functions. Thank you very much.
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9 views

bilinear regression (or broken power law) and non-detections (upper limits)

I am trying to figure out what is the best way to fit a set of two-dimensional data (x and y, presumably independent) with two segments of linear models and a ``break point''? The tricky part of the ...
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6 views

what do the outputs of usl model mean?

I am trying to understand the summary of the universal scalibility law model: ...
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20 views

One-Step estimators for non-linear regression

'Disclosure': This question is also asked in the economics.stack community, under the tag of Econometrics, with same title. I'm not sure if it's too technical for that community. Let's suppose I ...