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

learn more… | top users | synonyms (3)

0
votes
1answer
21 views

Heteroscedasticity in machine learning predictions

I am using a machine learning method (PLS) to predict a continuous variable, which currently does a pretty good job, with reasonable RMSE etc. However, the residuals exhibit heteroscedasticity, where ...
1
vote
2answers
22 views

Testing a single time-series for changing variance structure (Heteroscedasticity and Volatility Clustering)

I would like to assess a single time-series for a changing variance structure that might be leading to spurious variance estimates when that time-series is used in regression. In my head two terms ...
0
votes
0answers
11 views

How to calculate the effect size after Welch ANOVA?

I used oneway.test() because Levene's test indicated heterogenity of variance. Unfortunately, I don't know how to calculate the effect size now. Does anybody have ...
0
votes
0answers
15 views

how to test if 5 data are homogeneous or not significantlly different

I am currently analysis data of radionuclide content in soil profiles. I have different profiles and data every five cm depth. Each profile contains 5 values of a certain radionuclide. I can represent ...
0
votes
0answers
10 views

How can I check for collinearity and heteroskedasticity in mixed models with lme (package nlme)?

How can I check for collinearity and heteroscedasticity in lme (R package nlme)? I found a blogpost that provides functions to do so for package lme4, but not for nlme. Here's a minimal example ...
4
votes
1answer
55 views

Is an ANOVA applicable for these data?

I have a data set from 7 groups, with 20 fish in each group. Measurement of a parameter is made on 25 cells from each fish (so each observation in the data-set is completely independent, right?). ...
0
votes
1answer
17 views

Can the Breusch-Pagan test be applied to GLM?

I have developed a model to test if a relationship is unimodal by using a Gaussian GLM. In an effort to diagnose the various assumptions of linear models I used the Breusch-Pagan test to determine ...
0
votes
0answers
20 views

Chi-square approximation in homogeneity

I am interested in testing homogeneity in mixture of Gaussians (testing no mixture vs. 2 populations) given that we know the weights of the two distributions. We can first use MLE to estimate the mean ...
3
votes
1answer
40 views

Computational error on chi-square test for homogeneity

I have the following categorical data Control Treatment c1 285441 33296 c2 40637 4187 c3 737113 97433 c4 34036 3993 In other words, I have ...
1
vote
1answer
48 views

Problems when adding a variance structure into a GLMM

I did a GLMM model with proportional data using the lme4 package. This model has three categorical independent variables: Age (2 levels) Sex (2 levels) Status (2 levels) "Year" is the random ...
1
vote
1answer
44 views

How to calculate White-Huber standard errors by hand

I can't see how to replicate the calculation of WH standard errors for heteroscedastic data, as produced by the R packages sandwich / ...
0
votes
0answers
19 views

ANOVA for data does not fit the assumption of homogeneity of variance, which is better: ANOVA after ln-transformation or Welch's ANOVA

I have data, where many groups have different variance, so the data does not fit the assumption of homogeneity of variance. 1, First I ln-transformed all data, after all most of them had homogenous ...
0
votes
1answer
31 views

A comprehension question to conditional heteroscedasticity/GARCH

I have a time series with strong seasonality. At specific time periods/seasons there is also a stronger Variance than in other time periods/seasons. Is that an example of conditional ...
0
votes
2answers
63 views

Tests of heteroscedasticity in linear regression models

I am unfamiliar with the implementation used in the R package GVLMA. What are some basic tests of heteroscedasticity in linear regression models and how or where ...
0
votes
0answers
26 views

Comparing Variance Ratio tests to Hurst exponents

I have used the Chow Denning test and the Hurst exponent (Peng, Whittle and R/S methods) to examine if a particular time series follows a random walk. My results are conflicting between the 2 tests. ...
0
votes
0answers
22 views

Heteroskedasticity of error term in log-level models?

I am running a decomposition of log wages for two time periods and want to explain the variance of the error term. My question is: If there is a wage growth trend, will this automatically increase ...
0
votes
1answer
38 views

Is it important to model heteroscedasticity during multiple regression?

Given a multiple linear regression (eg. using a GLS procedure) between a response variable and several predictive variables with different, heteroscedastic relationships with the response variable and ...
1
vote
0answers
25 views

Address the problem of heteroscedasticity

I have 15 variables. The aim is to conduct Granger's causality test. I want to see whether I should Use log for all my variables. In order to check for the occurrence of heteroscedasticity, do I ...
2
votes
1answer
31 views

White's Test for heteroscedasticity Interpretation

I'm slightly confused as how to interpret the answers Stata is feeding me from the White's test. I am running two regressions: Regression 1 ...
4
votes
1answer
184 views

Fit regression model from a fan-shaped relation, in R

I get a fan-shaped scatter plot of the relation between two different quantitative variables: I am trying to fit a linear model for this relation. I think I should apply some kind of transformation ...
2
votes
0answers
35 views

Multiple comparison of non-normal, heteroscedastic data. What test should I use?

I have a set of brain pathology data. These were obtained by counting certain parameters in the brain. Due to availability of human brains, the amount of cases vary a lot across the different groups ...
1
vote
1answer
70 views

Estimating ARCH model using ML or OLS

ARCH(p) models are defined as: $σ^2 = a_0 + ∑a_ie^2_{t-i}+e_t$, $i>0$ Now, as with any VMA model, estimating this model using OLS/ML is impossible, because the error term is not observable. But ...
1
vote
0answers
26 views

Heteroscedastic censored regression

I am dealing with a heteroscedastic censored dataset. I tried to use the survival analysis package in R to estimate a linear model for it. So before doing that, I conducted a simulation study, where I ...
2
votes
0answers
48 views

Autocorrelation in DOLS: will HAC standard errors work?

I am currently estimating a cointegrating regression (DOLS), where my residuals have autocorrelation. Sometimes it is just in one or two lags, but sometimes it is more. My question is: Can I apply HAC ...
0
votes
0answers
48 views

Autocorrelation in squared residuals means heteroskedasticity?

I am wondering whether testing the squared residuals of a regression would provide information on whether there exists heteroskedasticity
2
votes
1answer
55 views

Are the statements “normally distributed with same mean and variance” and “identically normally distributed” equivalent?

According to Rohatgi & Saleh [1], random variables X and Y are said to be identically distributed if they have the same distribution function, i.e. $F_X$(x) = $F_Y$(y). Moreover, the ...
0
votes
0answers
36 views

Econometrics heteroscedasticity model

Consider the following model for real estate values applied to a cross-section of homes: ${\rm Price} = \beta_0 + \beta_1\cdot SQFT_i + \beta_2 \cdot YARD_i + \beta_3 \cdot POOL_i + \epsilon_i$ ...
0
votes
0answers
44 views

Non-normally distributed residuals for multivariate linear regression.Still a valid model?

I try to know if the independent variables are affecting the outcome of the dependent variable, but while the Shapiro-Wilk test shows residuals non-normally distributed, the autocorrelation of errors ...
0
votes
1answer
494 views

White's test for heteroskedasticity in R

I am trying to estimate heteroskedasticity in R. I had Eviews available in my college's lab but not at home. I have been trying to use "het.test" package and ...
1
vote
1answer
52 views

Forecasting a time series with conditional variance (heteroscedasticity) using Arima

I want to forecast a time series and have reason to believe that there are heteroscedastic errors/variance, which could be modelled with GARCH. However, I am not really interested in ...
0
votes
1answer
45 views

Can heteroskedastic residuals be justified by variance in dependent variable?

This is a very basic question and I hope it is not a duplicate. Im using a pooled regression model with a log-transformed dependent variable (electricity consumption meter values). The variance of ...
0
votes
0answers
17 views

Using Likelihood Ratio Test to deal with heteroscedastic data results in unreliable results

Suppose $Y$ and $x$ are not related. Therefore the linear regression analysis should not reject the null hypothesis ($H_0: b=0$) in $E(Y) = a+bx$. Suppose the variance in $Y$ increase with $x$ (i.e., ...
1
vote
1answer
44 views

Heteroskedasticity- is everything over for my model?

So, I've got this exponential model: Which, when tested via Pagan- Breusch, got heteroskedasticity detected. Breusch-Pagan / Cook-Weisberg test for heteroskedasticity Ho: Constant ...
3
votes
2answers
177 views

Error term in linear regression

I'm reading about a linear model which is fit to an equation, $Y = \beta_0 + \beta_1X + \varepsilon$, where $B_0$ is the intercept, $B_1$ the slope, and $\varepsilon$ the error term. My question is, ...
22
votes
3answers
2k views

Why are there two spellings of “heteroskedastic” or “heteroscedastic”?

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 ...
2
votes
1answer
98 views

Breusch-Pagan Test for ARIMA Model in R

I am testing my model using the Breusch-Pagan Test, but have not been able to find anything online regarding how to calculate it for an ARIMA Model. My AR1 Model is: ...
1
vote
1answer
44 views

Two way ANCOVA with slight heteroscedasticity

I am about to perform a 2-way ANCOVA but I reject the null hypothesis in Levene's Test with a p-value of 0.023. See standard deviation and sample sizes below. I googled up and down and found people ...
0
votes
1answer
27 views

Given a regression model with heteroscedasticity, find generalized least squares estimator?

I have $Y_i=\beta_0+U_i, E(U_i)=0, var(U_i)=2log|Z_i|, cov(U_i;U_j)=0$ when $i\neq j$. Suppose there are $n$ observations on $Y_i$ and $Z_i$. How do I use this information to find the GLS estimator ...
1
vote
0answers
19 views

Wild bootstrap v Pairs and model-based bootstrap

When calculating the standard errors of coefficient from OLS/Huber/LTS/LMS regression models on a data set showing some levels of heteroskedasticity, Paired and model-based bootstrap give rouhgly ...
1
vote
0answers
147 views

Regression Specification and Relation to Conditional Expectation Function

In their book, Mostly Harmless Econometrics, Angrist & Pischke introduce regression as an approximation to the conditional expectation function (CEF). They present (p 46) this equation: ...
1
vote
0answers
220 views

Unbalanced Panel data using R - Removing outliers and heteroskedastcity

I am new in R and it’s my first time using it so I’ll appreciate the help. I am estimating income elasticity for electricity consumption using budget shares. I have data for 8 regions categorized into ...
1
vote
0answers
29 views

Why does a robust linear model fitting give a residual standard error?

The way I understood when to use a a robust linear fitting is for example when your variance is not constant (e.g. when you have heteroscedasticity as shown with a Breusch-Pagan test for example) or ...
0
votes
1answer
52 views

How can I get a reasonable residual standard error for my linear model which faces heteroscedasticity?

My goal is to get the residual standard error of my model to be as small as possible. I have a linear model lm(y~x). When I plot the standardized residual errors in function of the explanatory ...
1
vote
0answers
57 views

Heteroskedasticity and autocorrelation in simple linear regression?

While looking through a simple linear regression, I noted the presence of both heteroskedasticity and autocorrelation, and am looking to understand the consequences of each. On this project, I am not ...
2
votes
0answers
70 views

When to use Brown-Forsythe Test?

I have been researching the differences between Welch ANOVA and Brown-Forsythe Test. I know that Welch ANOVA is used for more than two groups comparing whether there is statistically meaningful ...
0
votes
0answers
45 views

Should I include weights in LME?

I have two case studies where I am looking at the influence of a trait (trait A) on mortality (m) of trees and seedlings. Following your comments on ...
2
votes
1answer
74 views

Best way to deal with heteroscedasticity in R?

Originally posted on stackexchange but I was told that it fits better here. I have a plot of residual values of a linear model in function of the fitted values where the heteroscedasticity is very ...
0
votes
0answers
40 views

Breusch Pagan LM vs Engel LM

I am performing an event study and have identified 101 distinct events that I am analysing. Therefore, I am running 101 independent OLS regressions (GLS is not recommended in event studies), evaluate ...
1
vote
1answer
91 views

Consequences of violating assumptions of nonlinear regression when comparing models and/or datasets

I have a question about the consequences of using non-linear regression when the data violate the assumptions of (1) homoscedasticity and (2) normal distribution. Specifically, I am wondering about ...
1
vote
2answers
52 views

Homogeneity of variance is violated for z-scores but not for raw data?

Is this a normal thing to happen or have I done something wrong in SPSS? I am using a Levene's test.