Refers to the property of a random process to have non-constant variance along some continuum. This most commonly presents in regression where the error variance increases as a function of one or more predictors, but also commonly refers to a time series whose variance changes over time.
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1answer
156 views
Is there a better way to create variables with a certain correlation and one of them is heteroskedastic?
My goal is to generate two variable which are correlated and one of them is heteroscedastic with regards to an grouping variable.
To create two variables with a desired correlation the common way to ...
5
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2answers
126 views
Quantile regression and heteroscedasticity/autocorrelation
I hear it said [1] that QR makes no distribution assumptions about its error term.
Question 1: Does this mean that heteroscedastic and serially correlated disturbances do not effect the ...
1
vote
1answer
153 views
Isn't a test for cointegration the same as testing for heteroskedasticity in the residual error terms?
Testing for cointegration tests to see if the residuals from a regression between the two variables is a stationary process. So wouldn't a test on those residuals for heteroskedasticity be the same ...
1
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0answers
444 views
What to do after removing autocorrelation and heteroscedasticity in eviews?
I am empirically checking Fama & French three factors (market, SMB, HML - independent variables) model on a Viet Nam stock exchange. The dataset is daily stocks' return during almost 4 years. The ...
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0answers
150 views
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0answers
86 views
Robust regression: possible with ordered data?
I have two regressions to perform - one with a metric DV (-3 to 3), the other with an ordered DV (0,1,2,3). Neither normal distribution nor homoscedasticity is given. I have a two questions:
Some ...
2
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1answer
391 views
Different results of Engle's Lagrange multiplier test for conditional heteroscedasticity from SAS and FinTS
To fit a simple AR(5) model, I use SAS PROC AUTOREG. I called the option ARCHTEST=(QLM) which provides Engle’s Lagrange ...
4
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1answer
184 views
(Quantile regression) Which standard error for heteroscedasticity & serial correlation
I have heteroscedastic and autocorrelated residuals in my multivariate quantile regression model.
What's the quantile regression standard error estimator that's robust to this? Something hopefully ...
3
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0answers
208 views
Simultaneous heteroscedasticity and heavy tails in a regression model
I'm trying to create a prediction model using regression. This is the diagnostic plot for the model that I get from using lm() in R:
What I read from the Q-Q plot is that the residuals have a ...
8
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3answers
944 views
Advice on explaining heterogeneity / heteroscedasticty
I am looking for any help, advice or tips in how to explain heterogeneity / heteroscedasticity to biologists in my department. In particular I want to explain why its important to look for it and deal ...
2
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2answers
272 views
Question about homoscedasticity test
one of the reviewer of a paper of mine suggested to perform a homoscedasticity test between the results of two experiments, testing the same thing in two conditions. The experiments consisted in ...
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0answers
107 views
What would be the Variance of Intercept in case of heteroskedasticity? [closed]
Question is regarding Regression Analysis. what is the variance of intercept in case of heteroskedasticity?
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0answers
257 views
How to account for different degrees of familial relatedness in linear mixed model? Is heteroscedasticity a problem?
(Let me preface this by stating that I am somewhat of an R newb and also a LMM newb.)
I have a very, very simple research question. I have a continuous outcome variable ("HAPPY"). I have two factors ...
4
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2answers
346 views
Heteroskedasticity and standard deviation
I am looking at state-wide data (entire population) of a school's grade as a function of the school's poverty index. The data appears to me to be an unconditional heteroskedastic distribution. I am ...
0
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0answers
114 views
The statement of homoscedasticity of variance when describing the OLS model
In an applied econometrics paper, the author states the model to be estimated as:
Why does the author claim homoscedasticity? This isn't making sense to me; can't the population variance-covariance ...
8
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3answers
520 views
Regression modelling with unequal variance
I would like to fit a linear model (lm) where the residuals variance is clearly dependent on the explanatory variable.
The way I know to do this is by using glm with the Gamma family to model the ...
2
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1answer
350 views
Homogeneity of variance in regression
I have carried out simple linear regression and I am now checking the models meets the assumption of homogeneity of variance:
• am I correct in concluding that the Levenes tests which gave a ...
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2answers
791 views
Comparing the means of two time series
I have data sets of the returns of two indexes in the same market (two different sets of stocks constituting each index), with 496 observations for each. I want to compare if the means are ...
3
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0answers
106 views
Comparing model fit with heteroscedastic data
I am developing a physiological test using R that requires some parameters optimised. In comparing the new method against the existing method, the values of individual readings correlate in a linear ...
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0answers
186 views
Checking assumptions of regression - homogeneity of variance
I have made 9 models using simple linear regression. I'm now checking that each of models meets the assumption of homogeneity of variance. Each of the models used either categorical or numeric (year ...
3
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1answer
362 views
Do these residual plots indicate that my least squares regression coefficient estimates may be biased?
Lets say I have a linear regression: $$y \sim 1 + x_1+x_2$$
where the range of $x_2$ is $[0,10]$. I fit this model using lm or ...
2
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0answers
573 views
Non-normal and heterogeneous data with repeated measures ANOVA
I have run a repeated measures ANOVA using 3 groups and one factor with two levels.
I have discovered that the data are not normally distributed (but not badly), nor is the variance homogeneous in ...
0
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0answers
114 views
Robust version of GLS with regression weights in R?
Robust version of GLS with regression weights in R?
Hi all,
In the following webpage, I have expressed my concern about the heteroskedasticity in my residuals using rlm with regression weights in R:
...
4
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1answer
110 views
Modelling both mean and dispersion of count data
I have a model of the following form:
$P(Y \mid X) = \,D(\mu,\sigma^2) ~~\text{where}$
$\mu = f(X) ~~\text{and}~~ \sigma^2=g(X)$
where $y$ is the response vector of count data, $X$ is the predictor ...
5
votes
1answer
145 views
Linear regression with shot noise
I'm looking for the right statistical terminology to describe the following problem.
I want to characterize an electronics device that has a linear response
$Y = \beta_0 + \beta_1 X + \epsilon$
...
1
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0answers
181 views
How to check and correct heteroskedasticity in a multilevel model?
I've conducted an experiment in which we have registered a physiological measure (FR) of 30 participants in two different conditions. In each condition, I registered the measure in 20 time points, ...
3
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1answer
357 views
Are significance tests for the assumption of constant variance too strict when sample size is large?
My question is regarding linear regression and non-constant variance. I've heard that even though a large data set fails a normality test, this does not necessarily mean the data is not normal. This ...
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2answers
103 views
Estimating standard error of related regressions in R
I am working with regressions to understand the price creation of certain future contracts for commodities and try to explain it with other commodity pricese.
These future contracts have different ...
4
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2answers
4k views
How to run two-way ANOVA on data with neither normality nor equality of variance in R?
I am working on my master thesis at the moment and planned on running the statistics with SigmaPlot. However, after spending some time with my data I came to the conclusion that SigmaPlot might not be ...
4
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1answer
165 views
Is there a method to check the homogeneity of variance of a single time series?
I have a data frame with prices/dates, is there a method that checks if the variance is homogeneous during all the series? I know there are many test like fligner.test, bartlett.test but I need to ...
1
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1answer
683 views
I want to do an nested ANOVA but my variances are very unequal
I have data that were collected at a number of sites, and each site was located within one of three zones (Lake Ontario, Erie and the St. Lawrence), so I was hoping to do nested ANOVAs to compare ...
1
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2answers
516 views
Understanding the homoscedasticity assumption
I can't understand how this works:
$e$ is the error term and $x$ is the explanatory variable.
$$Var(e|x) = E(e^2|x) - [E(e|x)]^2$$
I know that $[E(e|x)]^2$ = 0 because $E(e|x) = 0$, and squaring 0 ...
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1answer
194 views
Heteroskedasticity-consistent Standard Errors for Difference Between Two Populations?
This is a homework question, so I am looking for help in getting the right idea so that I can execute the rest of the work on my own.
I have some data regarding military veteran status and ...
2
votes
1answer
273 views
Does a stationary process implies a normal distribution of the data?
My understanding is 'no', a stationary process does not imply a normal distribution of the data. However I haven't found a clear indication in my library or online. I am interested in other resources ...
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0answers
364 views
Heteroskedasticity, autocorrelation robust standard errors for SPSS
Is there a way of performing HAC robust standard errors in SPSS?
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2answers
2k views
When to use (non)parametric test of homoscedasticity assumption?
If one is testing assumption of homoscedasticity, parametric (Bartlett Test of Homogeneity of Variances, bartlett.test) and non-parametric (Figner-Killeen Test of ...
3
votes
3answers
1k views
Linear model Heteroscedasticity
I have the following linear model:
To address the residuals heteroscedasticity I have tried to apply a log transformation on the dependent variable as $\log(Y + 1)$ but I still see the same fan ...
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1answer
406 views
Can I use generalised least squares with a binomial distribution and a nested structure?
I'm trying to fit linear models to my data in R. I need to use a generalised least squares method as I have heterogeneity of variance in one of my variables. I was planning to use varIdent, as the ...
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votes
2answers
1k views
What are the dangers of violating the homoscedasticity assumption for linear regression?
As an example, consider the ChickWeight data set in R. The variance obviously grows over time, so if I use a simple linear regression like:
...
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1answer
742 views
On testing for heteroskedascity, some questions on the White test & Breusch-Pagan test
Isn't the test statistic for both tests identical? The only difference I see is that the alternative hypothesis is different. Since you don't need to know the function h in the Breusch-Pagan test, ...
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1answer
2k views
Calculate Newey-West standard errors without an lm object in R
I asked this question yesterday on StackOverflow, and got an answer, but we agreed that it seems a bit hackish and there may be a better way to look at it.
The question: I would like calculate the ...
2
votes
1answer
639 views
Heteroskedasticity in linear regression model & data transformation
pls correct me if i'm wrong. of the econometrics' literature i've read so far, most mentioned heteroskedasticity is not a major problem empirically but multicollinearity would pose a greater concern ...
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1answer
397 views
Help using maxFratio() in R (Hartley's test)
I found documentation at: http://hosho.ees.hokudai.ac.jp/~kubo/Rdoc/library/SuppDists/html/maxFratio.html
I am not sure how really to use this though and am coming up short finding help online.
If ...
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1answer
372 views
Why does the Breusch-Pagan test fail?
How Breusch-Pagan can't reject the null for a series like that?
...
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0answers
108 views
How to test homoscedasticity when the errors are DEPENDENT?
I have done a linear regression and plot the residuals. I noticed that the errors are dependent(autocorrelated), how could I test homoscedasticity of this series? I read that Breusch-Pagan test only ...
2
votes
1answer
111 views
How should I fit heteroskedasticity by group?
I am trying to fit panel data to a model of the form
$$y_{t,i} = \sum_{j} X_{t,i,j} \beta_j + \sum_k Z_{t,i,k} \gamma_{i,k} + \sigma_i \epsilon_{t,i},$$
where the regressors $X$ and $Z$ are observed ...
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0answers
92 views
Why to use fixed regressor in Breusch-Pagan?
I need to use Breusch-Pagan to check heteroscedasticity of my timeseries.
I found the explanation of the function, here: http://hosho.ees.hokudai.ac.jp/~kubo/Rdoc/library/lmtest/html/bptest.html
...
1
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1answer
191 views
Are HAC estimators used for estimation of regression coefficients?
The references I can find on HAC procedures (like Newey-West) in regression focus on the standard error of the estimated regression coefficients and hypothesis testing involving the same. I cannot ...
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2answers
204 views
ANOVA for non-normal heterogenous unequally replicated data
I need some advice on how to proceed with my data analysis. I have 3 groups (Archaea, Bacteria and Eukarya). Each group has unequal number of individual species (70, 651, and 244 respectively). Each ...
8
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2answers
4k views
Linear regression, heteroscedasticity, White's test interpretation?
I am trying to test whether my regression has an issue of heteroscedasticity. After running a regression, I can clearly see that the residual plot has a pattern. After taking a log of the dependent ...
