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Questions tagged [nonlinear]

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2
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1answer
24 views

When to use non-parametric regression such as kernel, generalized additive model, spline, and polynomial?

I understand that kernel regression is a form of non-linear/non-parametric regression. However, I know you can also use generalized additive models for non-linear regression, as well as polynomials ...
0
votes
0answers
18 views

Nonlinear data to use in multiple linear regression?

I am supposed to be running a multiple linear regressions to test my hypotheses. However, when first testing the assumptions that should be met before performing a linear regression, it turns out my ...
1
vote
0answers
18 views

non-linear tikhonov/ridge regularization?

For traditional ridge regression, the loss function is $loss\_function = ||A\mathbf{x}-\mathbf{b}||_2^2 + ||\Gamma\mathbf{x}||_2^2$ https://en.wikipedia.org/wiki/Tikhonov_regularization Is there a ...
0
votes
1answer
19 views

Can VARMA handle non-linear data?

I know that traditional ARIMA models cannot handle non-linear data but I was unable to find any place where it states whether if VARMA can handle non-linear data or only linear. Please clarify this ...
0
votes
0answers
13 views

Comparing two groups (nested) and differences between multiple dependent variables (nominal and continuous)

What is the best method to compare two groups in this situation? For example, lets say I want to compare and find differences between men and women. The independent variables can be nominal (own a car,...
1
vote
0answers
10 views

Primal solution exists but dual does not

I am working on the follwoing nonlinear model. Min z=10(1-$\exp$(−3x) ) subject to: x $\leq$ 3 When I solve this problem on LINGO, I got the message "dual solution does not exist but primal ...
1
vote
0answers
14 views

como eu posso ajustar parameteros um sistema com duas equações com a função nls()? [closed]

I Ned to fit this system of equations: I'm using nls.lm(), but want to use the nls() function # rm(list= ls()) df=read.table( text =" 0 0.010000000000000 0 0....
1
vote
0answers
16 views

Estimate the Beta Coefficients, and then find an algorithm

Referring to the photo, I need to report my beta coefficients as functions of observed Xi and Yi. I tried to reduce by taking the log of both sides but It seems I can't reduce this model because it is ...
0
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0answers
27 views
0
votes
1answer
21 views

Estimation of model with non linear dependent variable

I am trying to verify whether two variables are linked by a relation of the type: |y|=ax or y^2=ax. What could be the right statistical procedure to verify whether the above relations are correct and ...
0
votes
0answers
7 views

Non-linear parameter multinomial choice model

I am trying to develop a multinomial logit model with nonlinear parameter of the following form Here, dj represent a vector of proxy size variables for zone j and d is a corresponding vector ...
0
votes
1answer
43 views

SVM non-linear decision function using hyperline

Suppose that we have a toy classification problem X -> y in 2D. In scikit learn, I solve this question with X = np.array([[2, 1], [3,1], [3, 0], [4, 0], [5, -1]]) y = np.array([0, 1, 1, 1, 0]) from ...
0
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0answers
17 views

Variance of the mean in case of a quadratic trend

Please allow me to use Python code to put my question across. Suppose we want to model a variable using either a linear or a quadratic trend: ...
1
vote
0answers
55 views

cumulative distribution function for non-normal distribution

From this article, I read that the author drew four versions of CDFs each plotted in different distributions (all four plots come from the same sample data) From these four plots, the author chooses ...
2
votes
1answer
27 views

accounting for age effects: two age groups and within-group age differences

I am analyzing data from a study with two groups of about 25 healthy participants each, one young (mean age ~25 [~18-~30] years) and one older (mean age 59 [45-75] years). The study was set up mainly ...
0
votes
0answers
9 views

Usage of correlated (non-linear correlation) variables in an experiment and standardisation of variables values

The setting (see the dataset at the end of the question) The setting of the problem is this: I ask many multiple choice questions; only 1 out of the 3 available answers is correct; I ask the same ...
3
votes
0answers
37 views

Should I standardize my variable for regression before nonlinear feature transformation?

I would like to fit a non-linear model by doing nonlinear feature transformation first (e.g. exp, log) and then using linear regression (or regularized linear regression). However, I am stuck at ...
0
votes
2answers
43 views

Would machine learning techniques help if the linear and nonlinear relationships is so weak?

I have a cross sectional data set at hand contains four predictors to predict one outcome, I employed bivariate analyses to check whether the relationship between the dependent and independent ...
0
votes
0answers
11 views

High error value when estimating model parameters

I have a non linear system of ODEs and to estimate 4 of the model parameters I am using Matlab fmincon by minimising the sum of squared errors (SSE). I have only 5 ...
3
votes
1answer
60 views

Conterfactual estimation in machine learning model

There are various techniques to build counterfactual estimations of certain variables for linear models in observational studies. Some of those are based on comparing the change in the predicted ...
1
vote
1answer
62 views

How can I plot relationship between two variables with the constraint of initiating the S-shaped curve from (0,0) as depicted in the example below?

I don't want to run logistic regression or any such regression model. I have 8 to 10 pairs of data points and want to analyze the logistic growth model by fitting any function-generating S-shaped ...
0
votes
1answer
94 views

Neural network for predicting a non-linear function

I want to build a neural network to predict $f(x)=\exp(-x)$ for every $x$ in the interval $(0, 5)$. I randomly generated the training set uniformly in the given interval with 500K training examples, ...
4
votes
0answers
78 views

Can I statistically describe a single case/outlier vs. a distribution?

I have a dataset consisting of body weight and corresponding age for a bunch of healthy subjects (grey triangles below). I fit a nonlinear function to this data and graphed a 95% prediction interval. ...
0
votes
0answers
137 views

Using UMAP or other non-linear dimension reduction techniques on response variables prior to learning?

Background Suppose you have a training set where the response measurements are some $N$-dimensional vectors of related measurements - in my specific case, they happen to be cell viability scores for ...
0
votes
1answer
115 views

Which features should I choose to create polynomial features?

Sometimes we want to use some features in our original dataset to create polynomial features in order to add non-linearity to our model. The question is how to choose those features? Do we choose ...
2
votes
1answer
121 views

What is the difference betwen a time non-homogenous Markov Chain and a non-linear Markov Chain? Example

A time non-homogenous Markov Chain is one in which the transition probabilities are not constant over time. A non-linear Markov Chain is a model that is not linear in parameters and satisfies the ...
1
vote
1answer
99 views

How to test for overfitting in a TAR model in R?

I want to fit a threshold autoregressive model, and I'm using the tar package in R. For ARIMA models, I could check if a model was overfit by looking at the values of standard errors as compared to ...
1
vote
2answers
102 views

What is an appropriate transformation of an age variable when used as a predictor of athletic performance?

My question concerns using non-linear transformations on linear variables in regression, particularly where you believe the predictive weight might peak at some central value of the linear predictor. ...
1
vote
0answers
18 views

Linear Unconditional X-Y, Non-Linear Conditional X-Y

Intuitively, I can imagine that an unconditional (i.e., unadjusted for any covariates) Y~X relation can present as a linear relation, whereas a conditional Y~X|Z relation can present as a non-linear ...
1
vote
0answers
25 views

Exploratory factor analysis of a non-normally distributed data set with probable multicollinearity problems

I am trying to develop a scale measuring employee satisfaction regarding organizational support using spss. Most of my variables are positively skewed which should not be a problem in EFA as long as ...
1
vote
1answer
65 views

Fitting power model to data with zeros

I want to fit a power model to some data. The model is of the form y = ax^b. I can take one of two approaches: 1) I can take logs to linearize the model, and use linear regression to find values for ...
0
votes
1answer
70 views

Including error dependent on output in Gaussian Process Regression

I have a set of experimental data that I am trying to fit using Gaussian process regression (GPR) using Python's sklearn package. The only problem is that my data has an experimental standard ...
0
votes
1answer
316 views

R lmer, 3 time point longitudinal data, non linear, messy residual help!

I am new to mixed models so please go easy on me! I am attempting to longitudinally model a normally distributed continuous outcome with values in my dataset from -30-10. I have data collected at 1, ...
0
votes
1answer
61 views

upper confidence bound of a non-linear model seems wrong (predictNLS)

I have the following data and R-script: ...
1
vote
0answers
51 views

Tests to check a non-linear relationship?

I have a non-linear relationship between two variable (tested using a linear and square term). Are there any tests that can provide validation for the non-linear relationship? I have tested Lind-...
2
votes
0answers
47 views

Relevance of residual normally distributed residuals in nonlinear regression

I have a mathematical equation, based on physics, that requires estimating several parameters via nonlinear regression. I have conducted such nonlinear regression estimation with a dataset of 1100 ...
1
vote
0answers
146 views

Price Elasticity Estimation with a non-linear price schedule

How do I estimate price elasticity in a non-linear price setting? Non-linear prices are seen in utilities (electricity, water etc.) where the price per unit is determined by quantity purchased. So a ...
2
votes
1answer
1k views

Algorithms to model non-linear relationship between two vectors

I want to build a model that describes a curve that fits the data shown in the scatterplot. I thought it would be straight forward using sklearn. But the choice and application of the different ...
2
votes
2answers
383 views

Cosine-Similarity vs non-linear measures

In NLP, people often use cosine similarity to measure how close two vector spaces are to each other. However, we know that cosine-similarity is the same thing as Pearson correlation, for centered ...
4
votes
1answer
519 views

linear vs non-linear kernel SVM

The dataSet contains 213 examples of 7 classes . Each example are 25000 features. I want to learn model with SVM (test scenario used are 10-fold cross validation). I am a beginner in machine learning, ...
6
votes
4answers
207 views

Is R-squared truly an invalid metric for non-linear models?

I have read that R-squared is invalid for non-linear models, because the relationship that SSR + SSE = SSTotal no longer holds. Can somebody explain why this is true? SSR and SSE are just the ...
1
vote
1answer
77 views

Is log-log model considered to be nonlinear?

I am currently revising a paper, in which I tested an empirical model in the following form: , where EP is indicator of environmental performance, FDI - foreign direct investment which is the main ...
1
vote
0answers
34 views

Do I need to check for heteroskedasticity/heteroscedasticity only when performing regression analyses?

I don't know if this is a silly question but I haven't been able to find precise answer anywhere. I'm building a linear regression model in R to predict a variable of interest $y$, but there are also ...
3
votes
2answers
200 views

UMVU estimator for non-linear transformation of a parameter

Let $X_1, ..., X_n$ be iid. and $X_1\sim N(\mu,1)$. $\gamma(\mu)=e^{t\mu}$ for $t\neq 0$ My question is how to find an UMVU estimator for $\gamma(\mu)$ My concern is not so much about the specific ...
2
votes
1answer
342 views

Standard errors for non-linear least squares in R

I have a question on standard errors for non-linear least squares in R. With the built-in function NLS and a hand-made function I get different SE and I don't understand why. I will try to expose ...
1
vote
2answers
139 views

Nonlinear regressor in GLM link function

Try to reproduce Robert E. McCulloch and Ruey S. Tsay’s paper Nonlinearity in High-Frequency Financial Data and Hierarchical Models with local market data. the paper uses GLM to model high-frequency ...
0
votes
0answers
138 views

Hessian not positive definite but optim converges

I am using Optim routine to minimize a reasonably complex non-linear function. After completion of the optimization routine I am getting message codes as 0, that suggests optimization converged ...
0
votes
0answers
25 views

ARMA / ARMAX with nonlinear cross terms

Assume I have a multi variable ARMAX model. I would like to evaluate the influence of including cross products of the inputs. I could just calculate the cross products and include them as inputs for ...
5
votes
3answers
157 views

General approaches and techniques for developing good explanatory models for nonlinear data

Various recent efforts of mine on modelling some data through logistic regression have been... not successful. While there is still more data to look at, I've been wanting to explore nonlinear ...
1
vote
1answer
50 views

What data format should I use to learn the nonlinear output behavior of my guitar distortion pedal using a neural networkl?

My Problem I've built a very simple transistor guitar pedal. it has 1 mono input, 1 mono output. Now, all I have ever done in the past with ANN's is offline learning with labelled data and some work ...