2015年5月22日 · I frequently see both the spellings "heteroskedastic" and "heteroscedastic", and similarly for "homoscedastic" and "homoskedastic". There seems to be no difference in meaning between the "c" and the "k" variants, simply an orthographic difference related to the Greek etymology of the word. What are the origins of the two distinct spellings?

@Penquin_Knight has done a good job of showing what constant variance looks like by plotting the residuals of a model where homoscedasticity obtains against the fitted values. Heteroscedasticity can also possibly be detected in a plot of the raw data, or in a scale-location (also called spread-level) plot.

2015年8月8日 · Concerning heteroscedasticity, you are interested in understanding how the vertical spread of the points varies with the fitted values. To do this, you must slice the plot into thin vertical sections, find the central elevation (y-value) in each section, evaluate the spread around that central value, then connect everything up.

2015年6月14日 · White's Test for heteroscedasticity Interpretation. Ask Question Asked 9 years, 8 months ago.

Heteroscedasticity literally means "different amounts of scatter." It applies purely descriptively to data, for instance, where one subgroup of data may have a strikingly different spread than another (disjoint) subgroup. It may apply to time series (where it is a particular kind of failure of weak second order stationarity).

How can I adress problems of heteroscedasticity in mixed model analysis? Related. 5.

But if this is a question about remembering the meaning of those two funny words, just prepend them to sex and you will remember. Question 3: Heteroskedasticity means that x is correlated with the errors.

2020年11月30日 · In a regression setting and in econometrics, a fundamental distinction must be made between "conditional heteroskedasticity" (meaning, being a function of the regressors), and unconditional heteroskedasticity (meaning not being a function of the regressors). We are talking about a property of the "error" term.

2017年11月12日 · Heteroscedasticity more generally means non-constant variance, with reference to the mean. 1 case of that is that your absolute variance stays the same even as your mean shifts, as you pointed out. But your mean could stay the same and your variance could increase, or decrease, and either of those cases would also exhibit heteroscedasticity.

As far as 'heteroscedasticity' I thought I was using the word in the ordinary sense: "a collection of random variables is heteroscedastic if there are sub-populations that have different variabilities from others. Here "variability" could be quantified by the variance or any other measure of statistical dispersion."-Wikipedia.