Questions tagged [heteroscedasticity]

Non-constant variance along some continuum in a random process.

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Continuous, bounded response with decreasing trend in residuals for lme

My goal is to use a linear mixed effects model to test whether diurnality can be predicted by an animal's reproductive code, the season, and the fate of the animal at the end of the study period. All ...
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Show heteroskedasticity

Setup: Consider a random sample of size n with binary outcome $Y_i\in\{0,1\}$. Assume $Y_i\sim Bern(\pi_i)$. Use a linear probability model so that $\pi_i=X_i^\intercal\beta$, where $X_i$ is a ...
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Do we have to check heteroscedasticity when estimating quasibinomial model?

As we all know we are not interested in checking heteroscedasticity when estimating logit model when our variable is binary (taking only values 0 and 1). However do we also don't have to test ...
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Heteroscedastic errors in logistic GLM - a problem? [duplicate]

I am fitting a logistic GLM (assumed binomial distribution) with a random intercept and slope: DV ~ 1 + IV + (1+IV|subject) The DV is the number of successes of ...
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Presence of autocorrelation and estimation of coefficients [duplicate]

I am a beginner in quantile regression, quantreg package in R.I found that it is a good method to analyze data with outliers or non-normally disturbing data, but can´t find anything about ...
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How to handle Independent normal gamma densities with two precisions

I am given an independent normal gamma regression with group-wise heteroskedasticity: beta follows normal N(B_,V_) precision1 (h1) follows gamma G(s1^-2,v1_) precision2 (h2) follows gamma G(s2^-2,v2_)...
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Do these graphs fulfill assumptions of linear model?

Hi, I can see that there is a slight trend in the Scale-Location graph. I'm wondering if this is neglible enough to go ahead with a linear model? thanks! Eamon
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heteroskedasticity and logistic regression

I have cross sectional data and am using logistic regression. My question is how do I check my data for heteroskedasticity and in case it is present, then how to deal with it in Stata. I have come ...
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Why is a Breusch-Pagan test returning significant heteroskedasticity when the fitted value chart indicates homoskedasticity?

I was working the results of a regression equation and I wanted to test to see if there was significant heteroskedasticity in the residuals. Checking the results of the graph of fitted values versus ...
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Levene's test quadratic vs absolute - Difference?

I am doing an anova in matlab and to check for homogeneity of residual variances I want to perform a Levene's test. Matlab offers this handy function vartestn to do that. In the documentation there ...
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Do non-parametric tests depend on homoscedastic data?

I am finding myself having to perform non-parametric tests, primarily Mann-Whitney tests, on datasets which are not normally distributed. I notice that the datasets are not homoscedastic - do these ...
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What measure of heteroscedasticity is best for the use case of generating correlated data using gradient descent?

I am looking at generating datasets with correlated variables using gradient descent. There are already methods for generating correlated variables using Cholesky decomposition or eigenvalue ...
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Given the following heteroscedastic linear model, why we can assum E(W) = 1 without loss of generality

Consider a heteroscedastic linear model with data consisting of $n$ independent copies of $(Y,X,W)$, where $ Y\in \mathbb{R}^1, X \in \mathbb{R}^p, W >0$ is a weight with expectation one: $$ Y = u +...
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Post hoc test with heteroscedasticity

I ran an Anova using the car package. y~A*B+C A has 2 factor levels, B has 3 factor levels, and C has 2 factor levels (data from two data sets was included in the analysis. C is Experiment 1/2) I ...
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Standard error for panel data models and heteroscedastic robust SE

There is something I do not understand on a deeper level on standard errors for panel data models. I know the reason for not using usual heteroscedastic-robust standard-errors is because of auto ...
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Monte-Carlo Simulation for Quantile Regression

I am trying to perform a Monte-Carlo simulation using R. Currently I am getting stuck simulating the data. In a usual regression setting I would draw a random sample of the independent data and then ...
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Terminology: unconditional heteroskedasticity

I have seen mentions of both unconditional and conditional heteroskedasticity. The latter is fine with me but I am struggling to uderstand the former. It appears I am not the only one to question ...
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On the characterization of heteroskedasticity in our tag description

Our tag description for heteroskedasticity says Heteroscedasticity refers to the property of a random process that has non-constant variance along some continuum. This most commonly presents in ...
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Augmented Dickey Fuller (ADF) on Residuals

If I run an ADF on the residuals, and I get a result of stationarity, does it mean that the variance of the residuals is constant i.e. I should have homoskedasticity?
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Can I have heteroskedasticity in the residuals if the time series is stationary?

The time series is used in a regression (OLS) and then the diagnostics are been run. Or does stationarity imply homoskedasticity in all cases? I get heteroskedasticity through a breusch pagan test but ...
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Does this graph support an assumption of homoscedasticity?

Does this graphics support the assumption of homoscedasticity?
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Simple linear regression with skewness, kurtosis and heteroscedasticity

I have several issues with a very simple linear regression. I cannot get Skewness/Kurtosis and Homoscedasticity assumptions to be met, even after removing outliers, adding polynomial terms and using ...
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SEM Instead of MANOVA

I do not have sufficient reputation to comment on a question, so I hope this post is acceptable. Regarding the accepted answer to this question: How to do Simple Confirmatory Factory Analysis/SEM in R?...
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Can I conclude heteroskedasticity in this case?

I plot a standardized residuals against the fitted values and it does exhibit a megaphone shape. It looks like there is more variation in the lower level of fitted values. I then conduct a Breusch-...
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Test for equal variance of residuals for Nonlinear Regression Models?

I obtain a residual plot against the fitted values and it does show some pattern for the residuals, so I suspect there may exists heteroskedasticity problem. Which kinds of test can be apply here to ...
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Nonconstant Variance in Time Series

I'm studying ARIMA modeling right now for my online class. I tried using the auto arima functionality on EViews and it automatically log-transformed series 2 and 4, while for 1 and 3 just the first-...
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Homoscedasticity issues? And how to solve this?

Based on the plots attached. Do i have any issues with the homoscedasticity assumption? It looks like the dots on the scatterplot are spread but there is some sort of downward trend. Is this causing ...
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Can you help me derive the GMM (Generalized Method of Moments) estimator?

I have a question on GMM from a textbook that I am using to self study for an econometrics course I plan on taking next semester. Any help would be appreciated. Question: Consider the following moment ...
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Heteroscedasticity: When is it OK?

The point of the last analysis in my paper was to check on the basis of which predictor variables the answers to moral dilemmas can be explained. Predictor variables are continuous: dark personality ...
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How do I find out the change in standardized dependent variable when there is 1% change in the independent variable?

I am having a problem. I have to estimate a regression model and calculate the marginal effect of the independent variable on the standardized dependent variable. The model's specification must be ...
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What to fix first when testing for multicollinearity, autocorrelation and heteroskedasticity?

I have a Twoways "within fixed effects panel regression model and detected multicollinearity, autocorrelation and heteroskedasticity. For heteroskedasticity I want to use heteroskedasticity-...
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Assumption of Homogeneity of variance [duplicate]

Why is assumption of Homogeneity of variance required. What are the problems if they are not satisfied
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Forecasting a time-series with reference to another series

I'm trying to analyse the South African mutual fund industry returns over the last 40 years (since January 1980), however due to data limitations I was only able to obtain the monthly returns going ...
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Multiple groups' mean comparison with GLMM on unbalanced data with heteroscedasticity (glht)

I work in R with a data set containing a variable of interest (rv), a grouping factor (gg) and a random factor (...
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How Do I Create a Better Model?

Disclaimer: I am a senior undergraduate student of Political Science with little proficiency in Data Science; please help me understand better and forgive any ensuing statistical illiteracy! TL;DR: I ...
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Prediction of Mean and Variance with remlscore?

I would like to do a prediction of the mean and variance with confidence and prediction intervals using remlscore in statmod, i....
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Determine the proper level of heteroskedasticity

My dependent variable is house prices and I need to understand whether the level of heteroskedasticity in this plot of residuals vs fitted values is low enough to accept the existing multi-variate ...
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Comparison of variances with multiple factors using fligner kileen test

Hope my question fits in here and I have described everything well enough. Somehow I cant quite get my head around it. I have a data set with pesticide residue data in flowers, which had been obtained ...
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Test of sample mean when mean and variance are not independent

I have a dataset in which I have predicted risk probabilities from a survival model. The probability predictions were made at two different times for each observation - similar to a repeated measures ...
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Is there a decisive way of accepting/rejecting homogeneity and normality tests?

While learning about regression, I was told as a prerequisite for significance testing you must test for normality and homogeneity. I can do this by plotting Q-Q plots and residuals to fitted values, ...
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Heteroscedasticity across one dimension in a panel setting

I understand that in a regression setting, heteroscedasticity is present if the vector of residuals of a model has non-constant finite variance. Say you have a (balanced) panel across $i \in I$ and $t ...
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Breusch Pagan Test for individual factors

So if I have a multiple regression model and I want to test, which factors are related to the residuals using the Breusch Pagan test. If I use the bptest() function in R by regressing the squared ...
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Question about heteroscedascity and point estimates

Let's say I am running a regression: $y_{j}=\beta x_{j} + \eta_j$ and $var(y_i|x_i)=var(\eta_i|x_i)=f(x_i)$, say the variance is increasing in x. assume $\eta$ is fully independent of x, so ...
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Why is variance a fixed constant when modelling Linear Regression through MLE?

I was following a derivation of Linear Regression through MLE. Here we model Then we proceed to derive the negative log-likelihood through a series of steps as shown. Finally we maximize the above ...
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Best model for various bad situations

"What type of predictive model would best handle a wide variety of data issues. Extreme heteroscedasticity bi or tri modal distribution’s heavily correlated predictors… Saw this as an Amazon ...
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Are autocorrelation, heteroscedasticity and normality of residuals used in non-linear models?

I have a very simple non-linear model: lm(Y ~ poly(X, degree = 2), data=data) The results I obtained are: My question is, to test the validity of the model, is ...
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Do I need to check for Autocorrelation, Heteroskedasticity and Normality when building a model with data that are not time series? [duplicate]

I want to build a simple regression model with non-time series such as Client ID Number. when testing the validity of this model, do I need to check for autocorrelation, Heteroskedasticity and ...
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How do you check whether heteroscedastic-consistent estimators fix your error variance problem?

I am running an OLS regression, and have non-constant error variance (residuals vs fitted looks like a fan opening up to the right). I have tried a number of power transformation but they seem to make ...
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which test to do first? [duplicate]

I have a dataset that has 4 Columns as x axis. I want to check the data for: Autocorrelation, Multicolinearity, Heteroscedasticity and Normality, In what order should ı perform the tests? And ıf my ...
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How to calculate Newey-West adjusted covariance matrix?

I have a $T \times N$ matrix of asset returns, where $T$ = number of periods, and $N$ = number of assets. Calculating the covariance matrix of this set of returns is simple. How do I calculate the ...

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