Questions tagged [heteroscedasticity]

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

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Estimating heteroscedastic variance using a log transform and NN

In a paper I read, they are using a NN to estimate the heteroscedastic variance in a regression scenario (actually a bit more complicated than this, but irrelevant to the question). After they fit 1 ...
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Why is Ω unknown in GLS?

We run OLS and found the Homoscedasticity is violated and Hence, we go for GLS. But from variance-covariance of OLS's error - we have already found the Ω. Now, if we want to estimate β coefficients ...
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Differing statements Breusch-Pagan test vs. studentized Breusch-Pagan test

I am running a linear regression ...
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White test with neural networks in Python

I'm trying to apply the White test for heteroskedasticity to some neural network models in Python (https://www.statsmodels.org/dev/generated/statsmodels.stats.diagnostic.het_white.html). The built-in ...
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How to chose between transforming the data or applying a weighted regression when there is heteroscedasticity?

For long I have seen advice that, when the assumption of homoscedasticity is violated, one should transform the data or use weighted least-squares (see for example). But the advice (at least the one I ...
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Is it possible to know the actual covariance matrix, but fail to take-down heteroscedasticity and autocorrelation?

Is it possible to know the actual covariance matrix and estimate betas using $\Sigma$, but fail to defeat the problems caused by heteroscedasticity and autocorrelation and have biased or high-...
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Are the model residuals from GEE interpretable as residuals from simple linear regression?

Are the model residuals from GEE interpretable as residuals from simple linear regression, so that I may plot a residual versus fitted plot to determine whether there's heteroskedasticity? It is known ...
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Does the sandwich-estimate eliminate heteroskedasticity in a model residuals versus fitted plot, or simply make the estimation robust to heteroskedas? [closed]

Does the sandwich-estimator/Huber-White/GEE eliminate heteroskedasticity in a residuals versus fitted plot, or simply make the model robust to it?
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$\mathrm{E}\left[u u^{\mathrm{T}}\right]=\sigma^{2} I_{n} \text { is untrue } \iff \text{heteroskedasticity?}$

$\mathrm{E}\left[u u^{\mathrm{T}}\right]=\sigma^{2} I_{n} \text { is untrue } \iff \text{heteroskedasticity?}$ I know heteroskedasticity $\implies \mathrm{E}\left[u u^{\mathrm{T}}\right]=\sigma^{2} I_{...
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Is there any alternative way to Box-Cox transformations to stabilize the variance of a time series?

My question is straightforward: Is there any alternative way to Box-Cox transformations to stabilize the variance of a time series?
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Is there any test to check variance stationarity in time series?

The question is straightforward: Is there any test to check variance stationarity (homoscedasticity) in time series? And, if it exists, which are its implementations in R y Python? Thanks, Alejandro
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Help on GARCH-X model theory

I need to understand how a GARCH-X model (GARCH with explanatory variable) works. What I've understood so far is: we have a simple GARCH(1,1) model: If I add to the conditional variance equation an ...
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Do there exist welch's repeated measures anova/ancova/manova?

Do there exist welch's repeated measures anova,ancova for unequal variances or does one have to run a mixed-effects regression or friedman test? Is it possible to generalize this methodology to ...
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Heteroskedastic binary probit model

I am trying to implement a heteroskedastic probit model after the homoskedastic version using hetglm function in R. The main problem is to understand the criterion in choose the regressors that should ...
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State-of-the-art nonparametric $k$-way ANOVA allowing heteroscedasticity

QUESTION: Can you recommend a nonparametric version of a multiway ANOVA that is also robust in the absence of homogeneity of variances? So, this is what I am looking for: (1) Nonparametric ANOVA (no ...
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Techniques for addressing the homoskedasticity and normality assumption violations in mixed models with a non-all-positive response variable

I have a mixed model which the heteroskedasticity and normality assumptions for the residuals are violated. Up to this point, I have been addressing that by using the ...
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Assumption test in latent profile analysis (TidyLPA, R studio)

I'm planning on conducting an LPA of various personality traits and emotion regulation strategies however conducting after some hierarchal linear regressions beforehand I've found that many of the ...
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Which specific heteroskedasticity test is included in Python pmdarima auto_arima() results?

I'm using auto_arima() function from Python pmdarima library to determine the best ARIMA model. The results of one of my models ...
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Significant Levene-Test in Mixed ANOVA

I conducted a study to investigate the effect of instagram profiles on mood. Therefore I created two profiles on instagram and used a pre-post-measurement of mood (PANAS-scale). Participants (N=130) ...
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How to model a data with heteroskedasticity in variance and outliers in R?

I have a dataset where variance is different across groups, and there exist some outliers too. I used robust linear regression lmrob() to handle outliers. However, ...
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1 answer
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How to analyse a continuous data which is non-linear, heteroskedastic and is spatially autocorrelated?

I have data which is non-linear, heteroscedastic and is spatially autocorrelated. The predictor and response are continuous variables. Quantile regression accounts for the heteroscedasticity but I am ...
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Mediation Analysis: Does the homoscedasticity postulate is respected? If not, what can we do to solve that problem?

The purpose of my analyzes (with Rstudio) is to test the direct and indirect relations in a mediation model (to verify if the relationship between I_d and R_re_moy is mediated by U_moy). I_d is the ...
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How do I interpret the homoscedasticity of this?

Can someone help me interpret the homoscedasticity of this? My variables: Y: Depression, X: Anxiety, W: Gender
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Does this scatterplot indicate homoscedasticity?

Can anyone perhaps confirm if it is true that this scatterplot indicates that my data is homoscedastic? Since there are quite some more datapoints on the upper side, I was a bit hesitating. Thanks a ...
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Residual diagnostic for Boston Housing Dataset

I have some questions regarding the procedures for proper analysis of the "Boston Housing" dataset. My problem concerns the dysgnostics of the residuals and how to correct possible ...
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What is the variance of the error term for the regression of the sample mean of $x$ on the sample mean of $y$ that is heteroskedastic?

I am having difficulty finding an appropriate expression for the variance of $\bar{e}_{k}$ in $$ \bar{y}_{k} = \tilde{\beta} \bar{x}_{k} + \bar{e}_{k} $$ where $i = 1, \dots, n $ individuals from a ...
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Do asymptotic statistics "solve" the Behrens-Fisher problem?

The Behrens-Fisher problem concerns comparing two means from independent (maybe multivariate) samples in a way robust to heteroskedasticity in the populations being compared. It seems that if one ...
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Linear regression's (OLS) coefficient interpretation with heteroscedasticity

To use OLS for inference, is it necessary in all cases that the premise of homoscedasticity is met? I need to check the influence of some features (eg age, income...) on a variable y (whether or not I ...
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How to tell if data has homgenous variance? [closed]

I am checking the assumptions of ANOVA model and I want to see if the condition of homogeneity of variances is met in my model. I made such a plot, but I am not sure what to look at here and what ...
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Detecting homogenity of variance from the plot [duplicate]

I am checking the homogeneity of variance of my data (to check ANOVA assumptions). I don't really know how to interpret it though, does it mean there is a homogeneity of variance here?
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Error bars or standard deviation around means from zero-inflated heterogenous data?

I've constructed a plot of mean values per group (year) solely for the purpose of examining my data and have been told to always include either standard error (S.E.) or confidence intervals (C.I.'s). ...
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Distribution of true value when measurement imprecision is non-constant

What I believe to have understood so far (I am not a mathematician or a statistician, so please correct me if I'm wrong.) Say we are making measurements of some phenomenon $X$, and we have a normally ...
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Scale location plot interpretation

I ran a regular OLS regression and wanted to check if the assumptions for OLS regression was meet. To do this I plotted a scale location plot, but I'm struggeling with the interpretation of the result....
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2 votes
1 answer
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Kruskal-Wallis test on data with heterogeneous variance and small sample sizes per group

I've been trying to figure out how to test (in R) if there are significant differences between the group means of my data because it seems to violate the assumptions of tests that do this (ANOVA, ...
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Covariance matrix of errors for homoskedasticity/heteroskedasticity

I've seen homoskedasticty and heteroskedasticity defined as the following The error term of our regression model is homoskedastic if the variance of the conditional distribution of $u_{i}$ given $X_{...
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3 votes
1 answer
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Extreme Heteroskedasticity - Multiplicative Model - Strange residuals

I absolutely need your help with my research. When I checked for heteroskedasticity I obtained a weird result from the white test (p value = 0). When I plot the residuals, these are the results: ...
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1 answer
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Why is there heteroskedasticity even though no relationship seems present in the residual plot?

I estimated a random effects panel model and performed the Breusch-Pagan (BP) test for heteroskedasticity. The test is significant, meaning that there is heteroskedasticity. However, the residual plot ...
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How to build a regression equation for a gamma GzLM and how to interpret it?

I am trying to analyze if referral programs (1/0) have an impact on the average monthly spending of a user. I am confident that the gamma GzLM is the best model for my distribution: According to ...
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How to optimize transform function to make the variance and mode of the variance roughly stable?

$ curl -s https://i.stack.imgur.com/rl1eT.gif | tail -c +43 | zcat x y x2 2030667 x2 2343967 ... I have data like the above. If you compute the mean and ...
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Heteroskedasticity in OLS which best: clustered SE or robust SE?

I am trying to estimate the effect of a change in minimum wage regulation with no control group. I computed a propensity score for the probability of being affected by the change in MW before the new ...
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homoscedasticity violated or not?

I was wondering if the homoscedasticity in these two figures has been violated or not? Best regards, Elise
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Have my assumptions been met?

I am running assumptions for multiple regression and scatterplots are a real bane of mine. Can anyone advise as to whether the following scatterplot provides a linear or non linear relationship ...
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Do I need to transform/standardise my dependent variable?

Attached are the results and the residual plot for my regression of control variables on CEO compensation (TDC1). When I look at the plot my main concerns are the outliers (which I checked to be ...
1 vote
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Parametric bootstrap *prediction* interval with heteroskedasticity and sandwich parameter covariance matrix

The sandwich estimator for OLS regressions where heteroskedasticity is suspected is $$ var(\hat\beta) = (X'X)^{-1}X'ee'X(X'X)^{-1} $$ If I want confidence intervals on predictions, I can just take ...
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Calculating fixed effects in a mixed model with non-normality and heteroscedasticity with a 3-level time variable?

Due to non-normality and heteroscedasdicity, I use robustlmm and not lme4 for my mixed effects model. The variables look like this: ID: subject variable (random factor) var1: categorical between ...
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1 answer
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Is homoscedasticity an assumption for Pearson's correlation?

I'm running correlation analysis in SPSS between my variables and I'm starting by checking the assumptions to run Pearson's correlation (r). I'm confused as to whether or not homoscedasticity is one ...
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How can i check homoscedasticity for Level-2(between)-residuals in a twolevel model?

i have specified a random intercepts and slopes model with a Level 2-predictor for the intercepts on the between level. I have done the estimation with the lme4 package in R. Now, i want to plot the ...
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Heteroskedacity and non-normality - What to do?

I conducted an experiment in which I am trying to model the relationship between my response weed_coverage [%] and the predictors soil moisture [%] + treatment + distance. Weed_coverage and ...
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How to tell if there is a homoscedasticity of the model based on this plot?

I am building regression model of cholesterol predicted by 4 dietary components. I want to check if the assumption of Homoscedasticity is satisfied. I plotted Residuals vs Laverage plot. ...
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Heteroscedasticity in palaeolimnology with GAMs

I'm trying to understand heteroscedasticity and the influence this may have on GAMs fitted to palaeo data (or other time series). My understanding of heteroscedasticity is as follows (please correct ...
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