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Questions tagged [cooks-distance]

A measure of the influence of a single observation in regression modelling.

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Interdependence between leverages and residuals

According to the following online quote I read online: It’s worth noting that an observation can have a high absolute value for a standardized residual, yet have a low value for leverage. My ...
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Does Cook's distance follow an $F$-distribution?

The question is pretty much contained in the title: in a linear model $Y=X\beta +\epsilon$, with $\epsilon\sim N_n(0,\sigma^2 I_n)$, does the Cook's distance, defined as $$ D_i:=\frac{\frac{1}{p}||X(\...
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R Cook's distance vs leverage/(1-leverage) plot

One of the R plots for a diagnostic of linear model lm() is a plot Cook's distance vs. $\dfrac{h_{ii}}{1 - h_{ii}}$. My question ...
katryan's user avatar
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Explaining Cook's Distance

Does Cooks Distance tell us how much the estimated parameter values change when the ith observation is removed or how much the fitted values change when the ith observation is removed? I'm being told ...
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Cook's distance for GLM

In Applied Logistic Regression by Hosmer, Lemeshow and Sturdivant (2013), the formula for Cook's distance in a logistic regression is given as, $$\Delta\beta_j = \frac{r_{sj}^2h_j}{1-h_j}$$ where $r_{...
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Are the assumptions of collinearity and no influential observations relevant when all predictor (independent) variables are categorical?

In order to run a simple linear model (e.g. using lm() function in R) I am under the impression that the following assumptions must be met: Normality of residuals Homoscedasticity No collinearity (...
Insect_biologist's user avatar
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Analysis on Cook's distance when residuals are not normal

I have found in the slides of my course about linear regression a sentence that I couldn't understand properly which is the following one: "If residuals are not normal, analysis on Cook's ...
Andrea Suardi's user avatar
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Outlier in pearsons residuals after removing influential observations - How to remove?

I'm trying to run a GLM with multiple continuous preditor variables in R, cook's distance shows influential observations, I remove these and check my residuals for the model and have the outlier shown ...
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Cook's distance threshold in R

Short question: Which method is used in R to determine the threshold of the Cook's distance? For example in the demand '''ols_plot_cooksd_bar''' there is drawn a threshold line.
Marie Vermeiren's user avatar
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How to find 'influential points' in multivariate data with weak covariance

Part-1: I have used PCA and Mahalanobis distance to find outliers. But in both cases, only the highest or lowest values are detected as outliers. I am looking for a way that any data point that does ...
nothing to prove's user avatar
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Linear Algebra Treatment of Cook's Distance (or any situation involving deleting an observation)

I'm having trouble reconciling the idea of "deleting" a fitted value from a vector of fitted values in order to calculate the Cook's Distance. This notion is also troubling me in all of the ...
D.C. the III's user avatar
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Cook's distance for other then linear regression methods

I am curious when I can use cook's distance. I read here that it is only used for linear regression, but then on another site that it can be used for regression trees. So when is it appropriate to use ...
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Cook's distance, not plotting an observation with leverage one. What is this?

I am doing some regression diagnostics in R. I use plot() function and look at the four graphs. However, when I reach Cook's distance graph, I receive a warning ...
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Understanding Residuals vs Leverage plot in terms of meeting regression assumptions

Can someone help me understand the Residuals vs Leverage plot in terms of meeting the assumption of independence/influence for multiple linear regression models? My understanding is that the ...
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Addressing an observation which exceeds Cook's Distance

During my data analysis, I've been modelling the effect of 13 predictor variables on one response variable, house prices. When looking into possible transformations for my predictor variables, I was ...
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Is Cook's Distance a reliable way to find influential points?

I used Cook's Distance to identify influential points on several datasets and found model performance doesn't improve at all after removing them. So I wonder if Cook's Distance is a reliable way to ...
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Difference between DFBETA with DFFITS / Cook’s distance

A description of DFBETA is on the Wikipedia page: https://en.wikipedia.org/wiki/Influential_observation along with DFFITS and Cook’s distance. Cook’s distance and DFFITS are conceptually identical and ...
Single Malt's user avatar
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3 answers
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When to remove outliers?

I am currently doing a linear regression model. At the suggestion of my professor, we have looked at Cook’s distance to identify outliers. Here is the Cook’s distance plot using R. From what I ...
Kevin Falk's user avatar
9 votes
2 answers
3k views

Why the `cooks.distance()` function doesn't detect an obvious outlier?

I have the next plot: I want to detect outliers to delete them. I apply next code to detect them and delete them: ...
Dekike's user avatar
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1 answer
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The algebraic equivalence of two expressions for Cook's distance

I have read several times across different sources now that the definition of Cook's Distance, which is $$D_i=\frac{\sum_{j=1}^n(\hat{y}_j-\hat{y}_{j(i)})^2}{ps^2}$$ (where $\hat{y}_j$ is the jth ...
Quaere Verum's user avatar
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Finding the Case with the Highest Influence

I'm new to regression and diagnostics so if this seems a bit basic/unnecessarily long-winded that's why. I perform a multiple regression of a response variable on four predictor variables. There are ...
sandbag66's user avatar
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Cooks distance and categorical features

I try to detect outliers by cook´s distance for a regression. If I only use numeric features as explanatory variables it works fine. However, if I add categorical features to the explanatory features ...
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2 answers
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Identifying outliers in the data

Sample data ...
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Sensitivity Measures for GEE Model

Is there any method (e.g. like Cooks D) implemented in R to identify leverage points for GEE Models? I used geepack to fit my models and would like to do a sensitivity analysis now. However, I don't ...
geenieinabottle's user avatar
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1 answer
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Cooks Distance Confusion

I know there are a lot of questions along this vein, but none seem applicable to the data I have. Essentially I have run a one-way ANOVA using a variable composed of 4 different groups (A:D) and the ...
Blythe 's user avatar
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How to find an optimal combination of predictors in predicting outcome?

It is a marketing project in which I need to compare the effectiveness of six different marketing tools in terms of sales. the tools are like "No. of times a salesman personally visit to the customer",...
priya kansal's user avatar
8 votes
2 answers
19k views

Cook's distance vs. hat values

What exactly does Cook's distance measure? And how is this different from what hat values measure? I know hat values measure how distant a point it form its corresponding fitted point. I also know ...
Sara's user avatar
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2 answers
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A better Outlier Detection approach! [duplicate]

Currently I am using Cook's distance to detect outliers in multivariate data. Is there any better approach than Cook's distance for the same?
darkage's user avatar
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Can I use Cook's distance to detect outliers without a Dependent Variable?

I asked a previous question that I think was not worded well and long so I'm trying again! I have 3 different tasks and performance for 20 levels in each task, therefore, performance for 60 levels in ...
Trevor Dubois's user avatar
1 vote
1 answer
4k views

Should I remove the influential points in this case?

I build a linear model from a small dataset with ...
Iamsomean's user avatar
2 votes
1 answer
5k views

Plotting Cook's Distance Lines [closed]

I've currently created a plot using Python showing leverage vs residuals of some data. I want to plot Cook's Distance lines like shown in Case 2. How would I go ahead with this?
Flemingjp's user avatar
4 votes
1 answer
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Understanding Cook's Distance

I'm trying to use Cook's Distance in order to detect outliers in high-dimensional datasets. However, I've found some troubles in order to do such thing. Usually, once I've built the linear model and ...
asuka's user avatar
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1 answer
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Outliers in Linear Regression that ONLY revert significance

When doing linear regression, all sorts of influence checks (Cook's Distance, leverage, dffits, dfbetas, covratio) can be conducted on the data points. Each of these are literature-supplied with some ...
anspiess's user avatar
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2 votes
0 answers
588 views

How to calculate Cook's distance for `lm.ridge` objects in R [closed]

How can I calculate Cook's distance for lm.ridge objects? I first created a glmnet object and carried out ridge regression ...
Hindol Ganguly's user avatar
1 vote
0 answers
96 views

Justification for Dummy Variable When Cook's < 1

For a class project, I have a data set of restaurants and health inspection scores. I want to indicate if a restaurant was closed or not due to violations as this seems to be a significant predictor ...
anyspock's user avatar
5 votes
1 answer
2k views

Casewise diagnostics and testing assumptions for a mixed effect logistic regression in R

I am modelling a binary outcome (Buried), that has two predictors: Offset (a 3 level factor) and width (continuous predictor). In addition, multiple data points came from the same unit -- a chamber, ...
JeanDrayton's user avatar
2 votes
2 answers
455 views

What to do with an outlier that once removed prevent model convergence?

So, I'm performing generalized linear mixed models with a poisson distribution and an offset. When looking at the Cook's distance, I found gigantic values (above 3000). When removing the concerned ...
Emilie's user avatar
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4 votes
1 answer
513 views

Can Cook's distance plot only be used for least squares regression?

If Cook's distance can only be used for least squares regression, what are some alternatives that will give me a similar plot for a Gamma model or any regression model from the exponential family?
Vindication09's user avatar
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2 answers
1k views

How do I remove outliers in dataset?

I have a data-set (185 rows) with 20 predictors and 1 dependent variable. I have applied Cook's distance and then 4/N formula to remove some of the outliers in 1st iteration. Should I do this ...
Ahmad Shahwaiz's user avatar
7 votes
1 answer
2k views

Do points with high Cook's distance necessarily have a high standardized residual, and vice-versa?

I have two questions below: Could a data point be an influential point if its cook distance is outstanding(greater than 4/(n-p-1)) while its standardised residual is less than 2? It looks like to me ,...
whoisit's user avatar
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3 votes
1 answer
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Diagnostics for generalized additive model vs linear model

I am doing an analysis in R and I have the model: lm(birthrate~education+employment+lo(latitude, longitude),data=data2). It seems to be a generalized additive ...
Kristian von Riechstoffen's user avatar
2 votes
1 answer
256 views

Influential case - to remove or not to remove?

I'm doing a multiple regression analysis with 3 predictor variables (RELAT, SSS and FAITH), and the criterion variable is SSE. I have found that SSS is a mediator between RELAT and SSE, and FAITH is a ...
Simon's user avatar
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8 votes
2 answers
5k views

Cook's distance in detecting outliers

According to my understanding, Cook's distance measures the influence of each observation by excluding points when fitting a model. So I assume it could be an reasonable approach for outlier detection?...
Roy C's user avatar
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1 vote
2 answers
1k views

Inference of Cook's Distance Plot

What can we infer from cook's distance or the cook's distance plot of regression model? How can it be used to refine model further ? Should we remove the values which are high influencers or lie ...
Neo's user avatar
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3 votes
0 answers
129 views

Multiple Regression Assumptions

This may seem like a basic question, but I'm verifying the assumptions for a multiple regression and have some trouble wrapping my head around homoscedasticity. I have a few questions listed below: 1)...
Olivier's user avatar
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0 answers
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Outlier detection in multivariate data

I have a table with thirty variables and am interested in finding the outliers (rows). Assuming that my variables are independent I am hesitant whether I should use Cook's distance as it requires to ...
Michael's user avatar
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3 votes
0 answers
82 views

Is there a bound of percentage/number of influential points for a given size sample?

Consider for a given data set of size $N$, and we do a linear regression analysis on it. We know that we can define influential points among this dataset by setting a threshold value on the Cook's ...
Henry.L's user avatar
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2 votes
0 answers
335 views

Interpreting linearity in regression when there are outliers

I am trying to determine whether this regression meets all of the assumptions one needs to adhere to when carrying out a multiple linear regression. In looking at the residual plots below, it seems to ...
SilvanD's user avatar
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21 votes
1 answer
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Removing outliers based on cook's distance in R Language

I have this R code for linear regression: fit <- lm(target ~ age+sales+income, data = new) How to identify influential observations based upon cook's distance ...
user3459010's user avatar
3 votes
0 answers
440 views

Is it possible to derive Leverage figures without a Hat Matrix?

I ran into an impasse while attempting to write code for Cook's Distance: when a regression model reaches only a moderate size, I can't derive a Hat Matrix through my normal matrix math routines ...
SQLServerSteve's user avatar