Tagged Questions
6
votes
1answer
109 views
What does the residual higher level variance tell me?
I have a multilevel logistic regression model predicting the probability of item nonresponse, where the random intercept variance at country level takes on the following distribution for the different ...
1
vote
1answer
379 views
What is residual standard error?
When running a multiple regression model in R, one of the outputs is a residual standard error of 0.0589 on 95,161 degrees of freedom. I know that the 95,161 degrees of freedom is given by the ...
4
votes
3answers
157 views
What do normal residuals mean and what does this tell me about my data?
Pretty basic question:
What does a normal distribution of residuals from a linear regression mean? In terms of, how does this reflect on my original data from the regression?
I'm totally stumped, ...
2
votes
2answers
73 views
Summary of residuals in R
Disregarding "Deviance" in the image, the output of multiple regression analysis in R looks pretty much like this.
As far as I understand, residuals are errors. Do the 5 value summary refer to ...
2
votes
1answer
43 views
Explanation of a step in derivation of residuals for R lm diagnostic?
I'm reading Faraway's book (http://cran.r-project.org/doc/contrib/Faraway-PRA.pdf) to try to understand R's lm diagnostic plots. On page 72 of the book is this:
I have been trying to understand a ...
0
votes
0answers
87 views
Question about the validation step for a multinomial logit model
I've been skimming through a couple of books (all german ones, hence I do not cite them here) at what residual plots one should look at if the usual model assumptions in the context of a multinomial ...
0
votes
0answers
56 views
Which of the three residual plots shows the most evidence of a possible violation of any of the linear regression assumptions?
https://www.dropbox.com/s/a6oojun3rkvv9a6/Screen%20Shot%202013-01-25%20at%2011.53.07.png
https://www.dropbox.com/s/losw1w0raojq2he/Screen%20Shot%202013-01-25%20at%2012.09.06.png
Which of of the ...
0
votes
0answers
52 views
Forecasting volatility using HAR-RV, residuals are greater than predicted value
I have tried using the following model (HAR-RV) to forecast volatility:
...
3
votes
2answers
159 views
Troublesome residual plot from linear mixed model
I have fitted the following linear mixed model based on the results of an economic game:
lmer(TotalScore~perOOgivenP+Game+(1|Subject),REML=T,data=mdl1table)->m1
...
1
vote
1answer
74 views
residualize binary outcome variable
Does it make sense and what is the correct approach to residualize a binary variable? For a continuous variable y, I simply run a regression that predicts ...
6
votes
2answers
318 views
Influential residual vs. outlier
First, I should state that I have searched on this site for the answer. I either didn't find a question that answered my question or my knowledge level is so low I didn't realize I already read the ...
2
votes
1answer
69 views
RMS error of the SD line
Freedman's Statistics (p. 147 of the hardcover edition) says that if $Y$ is estimated using the SD line (rather than the regression line) then the RMS error of the residuals is ...
-4
votes
2answers
253 views
What does it mean in terms of regression if residuals are not white noise?
I need help in answering this one, it is an exam question.
2
votes
0answers
129 views
How to fix the constant variance assumption?
We have a project where we have to find the best model using a large set of data. In our current model there are 10 variables, some quantitative, and a few that are qualitative. When we first do ...
1
vote
0answers
253 views
Estimate of sigma squared in a simple linear regression when H0: beta = 0 is true
I was reading some lecture notes on simple linear regression where one section said that when the slope is 0 (hence, H0: beta = 0 is actually true), (SSY - SSE)/(DFY - DFE) estimates sigma squared. ...
1
vote
0answers
59 views
Estimating fixed effects for ordinal regression
I am running a model when the response variable (behaviour) is an ordinal factor (levels: 0,1,2,3,4) and I am testing the relationship with two fixed effect factors (year: A,B,C,D; colony; X1,X2).
I ...
3
votes
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 ...
2
votes
0answers
46 views
Transformation optimizing stationarity of the residual of a regression
I am trying to define an objective function or a method to find the transformation and coefficients optimizing the stationarity of regression's residuals.
For instance, if I want to regress $X_1$ vs ...
2
votes
1answer
321 views
How can we get different mean and median values for residuals when working with the same dataset?
Following this R instruction
> fit <- lm(spending ~ sex + status + income + verbal, data=spending)
I would like to calculate the mean and median of the ...
-5
votes
3answers
206 views
Getting started with analysis of residuals in linear regression
Since the mean of the residuals should be close to zero and with my calculations yield the following result:
> mean(resid(trees.lm)
[1] -3.065293e-17
is it ...
-1
votes
1answer
147 views
Two-stage linear regression
If I do regression in two stages:
Stage 1: $y\sim x_1 + 1$
Stage 2: resid_1st_stage $\sim x_2 + 1$
Will the resid_2nd_stage be orthogonal to $x_1$?
4
votes
4answers
276 views
Strange pattern of residuals
I am observing strange patterns in residuals for my data:
[EDIT] Here are the partial regression plots for the two variables:
[EDIT2] Added the PP Plot
The distribution seems to be doing ...
2
votes
2answers
543 views
Residuals for Logistic Regression and Cooks Distance
1) Are there any particular assumptions regarding the errors for logistic regression such as the constant variance of the error terms and the normality of the residuals?
2) Also typically when you ...
4
votes
2answers
3k views
How to understand standardized residual in regression analysis?
I have a stupid question. According to textbook, the residual is the difference between response and predicted value, then it is said that every residual has different variance, so we need to consider ...
2
votes
0answers
93 views
How do I satisfy the nonlinearity of my regression function with this plot image?
I have some problem with the transformation of my data. This is my project in my regression class, and we're asked to run our data and satisfy all the possible assumptions, until we can chose a model. ...
16
votes
3answers
310 views
Is it at all defensible to stratify a data set by the size of the residual and do a two-sample comparison?
This is something I'm seeing done as sort of an ad-hoc method and it seems very fishy to me but perhaps I am missing something. I've seen this done in multiple regression but let's just keep it ...
0
votes
0answers
344 views
Logical reasons for choosing regression through the origin
Is it reasonable to choose a regression model with a value of 0 for the intercept when this makes logical sense? For example, I am trying to model a physical ...
12
votes
4answers
982 views
Confirming the distribution of residuals in linear regression
Suppose we ran a simple linear regression $y=\beta_0+\beta_1x+u$, saved the residuals $\hat{u_i}$ and draw a histogram of distribution of residuals. If we get something which looks like a familiar ...
11
votes
2answers
6k views
How to read Cook's distance plots?
Does anyone know how to work out whether points 7, 16 and 29 are influential points or not?
I read somewhere that because Cook's distance is lower than 1, they are not. Am, I right?
1
vote
1answer
105 views
Why are the residuals computed manually different from those computed by R?
I have done a simple test using R, take a look at the code below:
First of all I have created three samples:
...
0
votes
0answers
290 views
Estimate absolute residuals in Stata
I have to regress the following equation in Stata:
$$R_{i,t} = \delta{i} + \sum_i \alpha_i*W_i + \sum_i \beta_i * R_{i,t−n} + \mu_{i,t}$$
I'm ok with this regression. My problem comes out when I ...
5
votes
6answers
1k views
Does it make sense to study plots of residuals with respect to the dependent variable?
I would like to know whether it makes sense to study the plots of residuals with respect to the dependent variable when I've got a univariate regression. If it makes sense, what does a strong, linear, ...
2
votes
1answer
94 views
Is it ok to bin residuals before examining them?
I'm analyzing the residuals from a regression model fit to a dataset that covers several years worth of data. I want to report the sum of the residuals from that model, by year, as a measure of how ...
1
vote
2answers
1k views
Predicted by residual plot in R
I'm wondering what the difference is between:
'predicted by residual plot' where I plot the residuals of the regression with the predicted values of the regression ;
the case where I plot the ...
0
votes
1answer
270 views
Is it enough to check residuals versus predicted values when assessing linearity assumption in multiple regression?
Is it enough to check residuals versus predicted values to see if the linearity assumption in multiple linear regression is satisfied?
Because for many predictors, you can't visualize the plot with ...
3
votes
0answers
162 views
Weighted regression for categorical variables
I have been trying to use weighted regression on some data where there are three categorical variables with the
lm(y ~ A*B*C)
command in R.
This was to try ...
3
votes
1answer
167 views
How is it possible that these variances are equal?
I'm using the Fligner-Killen test to analyze the residuals of a linear regression.
I subdivide those residuals in three groups and then I do the FK test to check the homogeneity of variances.
The ...
1
vote
2answers
1k views
How to analyze residuals of Poisson log-linear model?
I have bird count data and use classical poisson loglinear model, i.e. we have counts obs(i,j) - observed count for site i and ...
0
votes
1answer
317 views
Assuming $u\sim N(0,\sigma^2)$ when y is highly skewed
does it make sense to assume $u\sim N(0,\sigma^2)$ when I know from a histogram that $y$ is highly skewed. Because from the assumption $u\sim N(0,\sigma^2)$ it follows that $y\sim N(x\beta,\sigma^2)$ ...
2
votes
1answer
252 views
Looking at residuals vs. residual percentages
Suppose I fit a linear regression to some data (say, weight vs. height), and all the standard linear regression assumptions are satisfied (in particular, the data is homoscedastic). For example, ...
4
votes
2answers
458 views
Standardized residuals vs. regular residuals
I've got an easy question concerning residual analysis. So when I compute a QQ-Plot with standardized residuals $\widehat{d}$ on the y-axis and I observe normal distributed standardized residuals, why ...
4
votes
2answers
817 views
Why is R plotting standardized residuals against theoretical quantiles in a Q-Q plot?
In R, why do the default settings of qqplot(linear model) use the standardized residuals on the y-axis? Why doesn't R use the "regular" residuals?
3
votes
1answer
895 views
What kind of residuals and Cook's distance are used for GLM?
Does anybody know what the formula for Cook's distance is? The original Cook's distance formula uses studentized residuals, but why is R using std. Pearson residuals when computing the Cook's distance ...
5
votes
1answer
214 views
Weird residuals in linear regression
I analyze a set of multivariate measurements. It is known that several pairs of independent variables show high linear correlation. The graph below shows a scatterplot of one such pair (X and Y, upper ...
8
votes
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
votes
1answer
257 views
Algebraic definition of a residual from a regression
Can anyone give some advice on how to start proving this algebraically?
Define the residual from a regression (one independent variable) algebraically and show that:
the mean of the residuals is ...
4
votes
2answers
480 views
What does plotting residuals from one regression against the residuals from another regression give us?
I am working with the dataset of some heights and weights at different ages. My professor wants me to plot the residuals from regression of soma.WT9 against the ...
8
votes
1answer
575 views
LASSO assumptions
In a LASSO regression scenario where
$y= X \beta + \epsilon$,
and the LASSO estimates are given by the following optimization problem
$ \min_\beta ||y - X \beta|| + \tau||\beta||_1$
Are there any ...
4
votes
4answers
9k views
What is the expected correlation between residual and the dependent variable?
In multiple linear regression, I can understand the correlations between residual and predictors are zero, but what is the expected correlation between residual and the criterion variable? Should it ...
5
votes
1answer
3k views
Difference between Norm of Residuals and what is a “good” Norm of Residual
I am doing some basic fitting of data and exploring different fits. I understand that the residual is the difference between the sample and the estimated function value. The norm of the residuals is a ...
