Questions tagged [heteroscedasticity]

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

Filter by
Sorted by
Tagged with
1
vote
0answers
9 views

PERMANOVA: removing dominant species to avoid dispersion effect

Dear StackExchange community, I have an ecological dataset that contains several species from different sample sites. One species is extremly abundant that contributes 80 - 90 % to the entire ...
1
vote
0answers
12 views

Heteroscedasticity-consistent standard error is not the same as OLS standard error

Problem I perform the following regression $$ y_i = a + b x_i +\epsilon, \quad \quad i = 1, ..., 21$$ I managed to estimate $\hat a = −0.59$ and $\hat b = 0.069$ with standard error $s.e.(\hat b) = 0....
1
vote
0answers
5 views

How to decide whether to use robust errors in 2sls estimation

For my data, I have run both the OLS and IV regression to investigate the effects of health on salary. The BP test showed Heteroskedasticity for the OLS error terms so I decided to run the OLS ...
0
votes
0answers
3 views

Heteroskedasticity in cross-sectional data and time series data (volatility clustering)

With cross sectional data, it is fairly intuitive for me to understand Heteroskedasticity: Suppose you're regression $Y$ on $X$. For any given $X_i$, there will be multiple actual $Y_i$'s. There will ...
1
vote
1answer
29 views

VAR(p) Model in R with HAC estimator

I'm running a VAR model in R and found with several tests (arch.test, serial.test) that my model still contains ...
0
votes
0answers
8 views

How do I interpret this residual vs fitted graph for homogeneity of variance?

I am trying to interpret if homogeneity of variance assumption is right. can someone help me understand what does this graph say?
0
votes
0answers
22 views

Homoskedasticity

Suppose we have the following: $$Y=X_1'\beta_1+X_2'\beta_2+e$$ $$E[e|X_1,X_2]=0$$ $$E[e^2|X_1,X_2]=\sigma^2$$ $$E[X_2|X_1]=\Gamma X_1$$ We will assume $\Gamma\neq0$ and $\beta_1$ is of interest. We ...
0
votes
0answers
19 views

Is there an R function to fix heteroscedasticity in a series?

I did the heteroscedasticity test in a multiple regression (regresi_ri) and found out that my model had heteroscedasticity. How can I fix it? (without removing variables) heteroscedasticity
0
votes
0answers
35 views

Residual plot Diagnosis

I am working on a multiple linear regression model to investigate the relationship between several independent variables such as profitability, leverage, board size, percentage of women on board, ...
1
vote
2answers
46 views

Do explanatory variables have to have a linear relationship with the response variables?

Do explanatory variables have to have a linear relationship with the response variable in multiple linear regression? What is the reason for this assumption? Also, why are heteroscedastic ...
0
votes
1answer
32 views

Interpretation of plots of residuals vs independent variables in multiple regression?

I know that to check the homoscedasticity assumption in OLS regression, we plot residuals vs predicted values. However, Excel provides plots of residuals vs each independent variable. What is the ...
1
vote
0answers
54 views

Linear model with heavy tails

I am just approaching statistics and I find myself trying to fit different linear mixed models for my experimental data. My previous experience was mostly on lmer with binomial distributions, which ...
1
vote
1answer
36 views

How to account for heteroskedasticity in residuals in a fully crossed mixed-effects model (lmer)?

I’m new here so please let me know if I am missing anything in this description/explanation. I have a 4x4 repeated measures design. My dependent variable is pupil dilation, my two IVs are light level ...
3
votes
1answer
34 views

How to model conditional variance?

Sorry if this question has been asked before; I'd love to read any discussion around this. There's got to be a better way to summarize this question as well. I've got covariates $X$ and response $Y$, ...
0
votes
0answers
9 views

Homoscedasticisty in linear mixed model with interacting effects

I have conducted an experiment testing the effect of a drug on seizures across time in an animal model using R, my model being ...
1
vote
0answers
14 views

Estimating non-constant error function in a linear regression model?

Consider the non-linear regression model: $$ Y_i = g_1(X_i) + g_2(X_i) \varepsilon_i, $$ where $g_1,g_2$ are unknown, $X_i, \varepsilon_i$ are i.i.d. random variables with $X_i$ and $e_j$ independent ...
1
vote
0answers
28 views

What metrics can be used to evaluate each cluster in clustering

I am clustering a dataset, where the binary ground truth (positive/negative samples) is known. I am looking for specific clusters that show high homogeneity/purity. I know that there are many metrics ...
1
vote
0answers
15 views

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 ...
0
votes
1answer
24 views

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 ...
0
votes
0answers
7 views

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 ...
0
votes
0answers
27 views

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 ...
0
votes
0answers
7 views

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 ...
2
votes
0answers
20 views

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
2
votes
2answers
51 views

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 ...
0
votes
1answer
46 views

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 ...
0
votes
0answers
29 views

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 ...
3
votes
1answer
84 views

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 ...
0
votes
0answers
9 views

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 ...
0
votes
0answers
65 views

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 +...
0
votes
1answer
28 views

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 ...
1
vote
0answers
18 views

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 ...
1
vote
2answers
75 views

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 ...
6
votes
1answer
247 views

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 ...
2
votes
0answers
30 views

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 ...
0
votes
0answers
13 views

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?
0
votes
1answer
82 views

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 ...
0
votes
1answer
37 views

Does this graph support an assumption of homoscedasticity?

Does this graphics support the assumption of homoscedasticity?
0
votes
0answers
94 views

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 ...
1
vote
1answer
70 views

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?...
3
votes
0answers
21 views

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-...
0
votes
0answers
18 views

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 ...
0
votes
0answers
8 views

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-...
1
vote
1answer
63 views

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 ...
0
votes
0answers
17 views

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 ...
0
votes
0answers
52 views

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 ...
0
votes
0answers
6 views

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 ...
0
votes
1answer
54 views

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-...
0
votes
1answer
26 views

Assumption of Homogeneity of variance [duplicate]

Why is assumption of Homogeneity of variance required. What are the problems if they are not satisfied
0
votes
1answer
20 views

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 ...
1
vote
0answers
9 views

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 (...

1
2 3 4 5
20