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Questions tagged [nonlinear]

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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 ...
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1answer
14 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 ...
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0answers
15 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: ...
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0answers
20 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 ...
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1answer
26 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 ...
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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 ...
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0answers
29 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 ...
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2answers
42 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 ...
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0answers
10 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 ...
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1answer
54 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 ...
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1answer
53 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 ...
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1answer
79 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, ...
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0answers
76 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. ...
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0answers
82 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
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1answer
62 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
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1answer
91 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 ...
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1answer
80 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
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2answers
67 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. ...
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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 ...
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0answers
22 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
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1answer
55 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
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1answer
42 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 ...
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1answer
224 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, ...
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1answer
42 views

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

I have the following data and R-script: ...
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0answers
45 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-...
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0answers
40 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 ...
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0answers
90 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
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1answer
836 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
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2answers
283 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
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1answer
390 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, ...
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4answers
192 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
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1answer
61 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 ...
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0answers
32 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
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2answers
170 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 ...
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1answer
202 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 ...
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2answers
111 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 ...
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0answers
113 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 ...
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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
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3answers
148 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
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1answer
46 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 ...
0
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0answers
36 views

Is it possible to test all combinations of my non linear least square model with AIC

I have just started my stats analysis for my master and since stats is not my forte, I need help. I'm testing how a DOC gradient can affect MeHg bioaccumulation (BAF) in zooplankton. The theory says ...
2
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1answer
55 views

Non-linear relationship among independent variables in linear model

Assume that we have a linear model with 4 independent variables, and 2 of them have a strong non-linear relationship (between them). How this fact could affect my model ($R^2$, or implications on the ...
0
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0answers
24 views

non linear relationshipt between two variables

I am analyzing the relationship between two variables, x and y, and a scatterplot reveals basically not visually recognizable patterns (a big flat cloud), but including a regression line shows a ...
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0answers
92 views

Singular value decomposition

Can singular value decomposition used to impute missing values in highly nonlinear process under multiple input and multiple output behavior?
15
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2answers
774 views

If an auto-regressive time series model is non-linear, does it still require stationarity?

Thinking about using recurrent neural networks for time series forecasting. They basically implement a sort of generalized non-linear auto-regression, compared to ARMA and ARIMA models which use ...
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1answer
55 views

Using Iterative Gradient Descent to Determine to determine the Transformation for a Registration Algorithm

Based on the paper "Iterative Estimation of Rotation and Translation using the Quaternion" I am trying to define find the transformation, i.e. the rotation and scaling, that registers points from the ...
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1answer
106 views

Non-linear VS non-normal

Are they same? I know they are absolutely different due to the different concept, but a paper said they are same. Is it true?
0
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1answer
63 views

Is my model linear or non-linear

I was going through the following discussions Is this a linear or non linear model, and why? How to identify models as linear or non-linear? In the above discussions, users have submitted some ...
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1answer
137 views

Identification of a Heckman Model through Nonlinearity

I often read that the standard Heckman selection model is identified from the non-linearity of the Mill’s ratio. I don’t fully understand why linearity (or lack of) determines identification. From ...
3
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1answer
2k views

What exactly happens when I do a feature cross?

I was going through a machine learning course and they talked about combining various features to create synthetic feature to take care of non linear data. For eg in the below picture I didn't do any ...