Questions tagged [heteroscedasticity]

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

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how to check heteroskedasticity in pyhton?

After building model by using glm. How to check heteroskedasticity? are there any tests available to find or is it checked by using graphs??
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When distributions are non normal and heteroscedastic, is it preferred to use ordinal logistic regression or permutation tests?

I am currently conducting statistical tests on my two independent samples (both with more than 1500 entries each). The sample sizes are no equal. My response variables are interval as well as quasi ...
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Statistical analysis of data heteroscedasticity and non-normal residuals

I am dealing with a data set that contains a continuous positive response variable (weight of a beetle that feeds on plants) and two treatments (categorical variables with each 2 levels). It's a ...
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42 views

Homoscedasticity and relationship to error/residuals

My understanding is that homoscedasticity is related to the unobserved error, e.g., $\epsilon$ in the model $Y = X\beta + \epsilon$, and not the residual, i.e., $r = Y - X\hat{\beta}$. If this is the ...
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Why does PCA require/benefit from homoscedasticity?

Why does PCA specifically (and dimensionality reduction methods in general) require that the variance remains constant across the different values of the mean? An explanation not relying on strong ...
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Calculating group-level mean with varying group sizes for micro-macro data structure

My study is designed in such a way that I have individuals with varying numbers of observations of the predictors, but only one observation of the outcome. Like a multilevel model, but with the ...
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1answer
24 views

How can the below graph be interpreted

How can you interpret the scale location graph in terms of Homoscedasticity?
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1answer
129 views

Neural Network Assumptions in a Time series

I was wondering whether an artificial neural network regression, like ARIMA, requires statistically insignificant residual autocorrelation -- and, if so, why? I presume that, if I am using the ANN ...
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1answer
128 views

Difference between heteroscedasticity and ARCH effects?

What is the difference between heteroscedasticity and ARCH effects? For example in R you can do a Breusch-Pagan Test to test for heteroscedasticity, and a Lagrange Multiplier (LM) test for ...
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What is the reason for using Fligner-Killeen test on non-normal data, if ANOVA requires more or less normality? What are the other applications of it?

Variance homogeneity tests like Bartlett or Levene assume approximate normality of the data among groups. That makes a lot of sense, if we the tests before running ANOVA, which wants the normality as ...
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Lognormal GLM and variance estimation

I'm modeling an outcome with a positively-skewed distribution. I have chosen to use a GLM with a lognormal distribution and the identity link. Note: I am not log-transforming the outcome variable ...
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54 views

I think my data is heteroscedastic but I would like another opinion if possible?

Thank you for looking at my question, I've been driving myself a little crazy over it today! I have run tests for the assumption of homoscedasicity however I have been deliberating whether the ...
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66 views

Data transformation to deal with heteroscedacity

I am trying to build a linear regression model of the data which generally looks like this: Certainly due to the exponential (I guess) nature of the data, I have tried to do a logarithmic ...
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78 views

How to use HAC errors in VAR model

I would like to use the Newey-West method for the standard errors in a VAR(p)-model (I use statsmodels.tsa.vector_ar). The VAR(p)-model assumes that the residuals ...
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24 views

How to handle violation of Homoscedasticity

It seems that my model doesn`t follow the assumption of Homoscedasticity(simple linear regression). How should this issue be handled?
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59 views

Heteroskedasticity tests: heavy-tailedness of squared estimated errors

I have a time series model and obtain the following distribution of estimated errors: I suspect that the errors are heteroscedastic in the sense that their variance depends on the level of one or ...
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1answer
63 views

Is a nonlinear regression model valid even if it not Homoscedastic?

I have a couple of experimental datasetsa where I am trying to determine if there is, for each data set, a particular linear/nonlinear regression model that correlates both variables. To this end, I ...
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131 views

Is assumption of residual normality and Homoscedasticity in nonlinear regression

I am still learning a lot about nonlinear regression and I have some questions about residual normality and Homoscedasticity: 1) From what I could find here (Consequences of violating assumptions of ...
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1answer
36 views

How to do a levene's test without a grouping variable?

I have a list of people who did a test before and after an intervention. And I want to compare their pre- and post-scores. Now before I do t-tests, I have to check for heteroscedasticity with a levene ...
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1answer
221 views

Is this Residual-vs-Fitted-Plot showing homoscedasticity or heteroscedasticity?

I have a regression model. I checked it with hettest (test for heteroscedasticity) in Stata and it gave me an insignificant result; thus no heteroscedasticity. But ...
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1answer
362 views

Contradictory results between Breusch-Pagan test and Goldfeld-Quandt test in Python

I am reading Python regression diagnostic for statsmodel in Python. Under the heteroskedasticity tests, they introduced two test: the Breusch-Pagan test and the Goldfeld-Quandt test. From my ...
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106 views

Generalized Least Squares for linear regression with continous and categorical predictors

I have a linear regression model in R studio with a continous and a categorical predictor, where the assumption of homoscedasticity is violated: ...
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How to fit the data with both Ridge and Robust regressions

I have a set of data that has multicollinearity and heteroscedasticity. I understand if the data only have multicollinearity we can use ridge regression or I can use the VIF indicator and remove the ...
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35 views

Heteroskedasticity testing with Breusch-Pagan in R, two functions — very different answers?

I am currently testing two different functions in R to determine heteroskedasticity in a regression model with 4 predictors, 2 continuous and 2 categorical. One function is telling me there is a high ...
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26 views

Gauss- Markov Efficiency?

if I have a ragression model $y_i = x_i\beta + u_i$ were I know that the square of error have this $u^{2}=\gamma w^2_{i}+\epsilon_{1}$, where I know only that $E(\epsilon_{i}|w_{i})=0$, $E(u_{i}|w_{i}...
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Question about notation for constant variance

In the context of linear regression where there is an assumption of "constant variance" I have read this: $$\mathbb{V}(\epsilon_i \mid X_i)=\sigma^2$$ But there are two ways I can read this. Either $...
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Testing for homoscedasticity using the Breusch Pagan Test

I am trying to figure out how to test for homoscedasticity. But run into a small issue. I am using this r-bloggers article as a learning resource. According to this article there is no ...
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42 views

Adjusting standard errors for *both* heteroskedasticity and clusters in MATLAB?

My data is not exactly a panel, so I can't use the Panel Data Toolbox. It is over time (years) but not for the same industries. For example I have multiple rows with same industry in one year, and ...
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Why do heteroscedasticity-robust standard errors in logistic regression?

I am following a course on R. At the moment, we are working with logistic regression. The basic form we are taught is this one: ...
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47 views

Dealing with Heteroskedasticity in Estimated Dependent Variable model

I work on my research in finance concerning pricing of green bonds and I am running a two stage model. Stage 1 regression is an unbalanced panel fixed effects estimation. For each of my 100 green ...
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why arima uses differencing transform not the log transform to make data stationary?

I am currently working on time series project and i am naive. I would like to ask, there exist strict stationary, differencing stationarity. If i understood correct the first order differencing ...
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119 views

Heteroscedasticity in GLMM

I'm after some advice regarding heteroscedasticity in a residuals vs predicted plot. I have measured the length of a group of animals at birth and then at five subsequent time points into the future. ...
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variance of beta 1 OLS homocedastic v/s OLS robust

Hi i would like to demonstrate this but I could not. firstly we know that $var(\hat{\beta}_1^{homo})=\frac{\sigma^2}{\sum(x_i-\overline{x})^2}$ in the homoskedastic model. Secondly, we also know that ...
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82 views

Variance stabilizing transformation for time series

I differenced the time series and got this plot. I think I'm supposed to use a variance stabilizing transform because variance is increasing over time but I'm a bit confused as to which one I'm ...
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387 views

Is there ever a statistical reason NOT to use Satterthwaite's method to account for unequal variances?

Two related questions: 1) From what I've read, using Satterthwaite degrees of freedom does not assume equal variances, which allows it to be used on datasets that would be inappropriate for, say, a ...
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50 views

Algorithm for dynamic linear regression with stochastic volatility?

Is there any paper or textbook on how to estimate dynamic linear regression model with stochastic volatility? The observation equation and state equation, $$Y_t = \beta_t'X_t + \epsilon_{t}$$ $$\...
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26 views

Weak stationarity with conditional heteroskedasticity

The standard definition of weak stationarity is constant mean, and the covariance is shift-invariant - which I read to imply constant variance? But I've seen GARCH processes described as weakly ...
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1answer
83 views

Dealing with violation of OLS assumptions

I am currently writing my Master's thesis in economics. I am analyzing the second home rate in Swiss municipalities in R. The second home rate for municipality $j$ is defined as the share of the ...
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Comparing means with unequal variances

I have a dataset (n = 451) of integers split into six uneven groups and was hoping to run a version of a one-way ANOVA to compare means, but I'm struggling with meeting the normality and equal ...
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Why is homoscedasticity (homogeneity of variance) important in neural network layers?

I'm studying the famous Xavier initialization paper (Understanding the Difficulty of Training Deep Feedforward Neural Networks (Glorot and Bengio, 2010)) and had a question. When they explain the ...
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How much heteroscedasticity need to be present in order to justify the use of robust standard errors?

Im trying to figure out if my data is heteroscedastic and if I need to use robust standard errors (Huber-White standard errors). The dataset contains 70 000 rows and 5 columns. Y is a numeric ...
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1answer
89 views

How does taking the log of the variable solve our problem of heteroscedasticity?

I have been taking online classes on linear regression, and in that the instructor told that heteroscedasticity can be solved by taking log of the variables, I was not much acquainted with the ...
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2answers
961 views

Analysis of variance for nonnormal data with unequal variance

I would like to ask whether it is possible to perform an analysis of variance on data that is not normally distributed and has unequal variance, but I have large enough sample size. I have read that ...
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1answer
210 views

Residuals and Homoscedascity in SEM with lavaan

I intend on investigating longitudinal effects through a cross-lagged panel design, facilitating the lavaan package in R. Currently, I have set up a simple Model given the scheme and code below, in ...
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How to split residuals into groups for the Brown-Forsythe test

I have the following data id: 1 2 3 4 5 6 7 8 9 10 11 12 num. responses(predictor): 16 14 22 10 14 17 10 13 19 12 18 11 cost(response): 77 70 85 50 62 70 55 63 88 57 81 51 I fitted the linear ...
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1answer
61 views

Breusch-Pagan Test for Heteroskedasticity, what is the correct form of the null hypothesis?

For the Breusch-Pagan Test, under pg. 4 of this resource It claims that the null is $$ H_0: E(u\mid X) = \sigma^2 $$ But here it is stated that the null can be written as $$ H_0: \delta_1 = \...
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54 views

Test of homogeneity for Odds Ratios in conditional logistic regression analysis SPSS

I'm doing a case-control study, and I have made stratified analyses based on two age groups, as well as subtype of the type of cancer I'm doing my research on. My exposure of interest seems to be ...
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1answer
62 views

Do these graphs show that the regression assumptions are met?

Is there any concern regarding this plot, specifically that it meets the homoscedasticity assumption? May I continue with multiple linear regression? How can I fix this? My research is on household ...
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1answer
53 views

what is meant by: heterogeneous residual errors and homogeneous residual errors

what is meant by: heterogeneous residual errors and homogeneous residual errors. I am reading a paper that says the following: ...
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1answer
1k views

Breusch and Pagan Lagrangian multiplier test for random effects for Random effect heteroskedasticity

I'm really confused about Breusch and Pagan Lagrangian multiplier test for random effects. The command in stata is xttest0. Some say it is a test to choose between random and fixed effects and ...

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